Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(support vector machines). Showing records 1 – 30 of 493 total matches.

[1] [2] [3] [4] [5] … [17]

Search Limiters

Last 2 Years | English Only

Degrees

Levels

Languages

Country

▼ Search Limiters


University of Hong Kong

1. 旷章辉; Kuang, Zhanghui. Learning structural SVMs and its applications in computer vision.

Degree: PhD, 2014, University of Hong Kong

Many computer vision problems involve building automatic systems by extracting complex high-level information from visual data. Such problems can often be modeled using structural models,… (more)

Subjects/Keywords: Support vector machines; Computer vision

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

旷章辉; Kuang, Z. (2014). Learning structural SVMs and its applications in computer vision. (Doctoral Dissertation). University of Hong Kong. Retrieved from Kuang, Z. [旷章辉]. (2014). Learning structural SVMs and its applications in computer vision. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5223970 ; http://dx.doi.org/10.5353/th_b5223970 ; http://hdl.handle.net/10722/206663

Chicago Manual of Style (16th Edition):

旷章辉; Kuang, Zhanghui. “Learning structural SVMs and its applications in computer vision.” 2014. Doctoral Dissertation, University of Hong Kong. Accessed February 23, 2020. Kuang, Z. [旷章辉]. (2014). Learning structural SVMs and its applications in computer vision. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5223970 ; http://dx.doi.org/10.5353/th_b5223970 ; http://hdl.handle.net/10722/206663.

MLA Handbook (7th Edition):

旷章辉; Kuang, Zhanghui. “Learning structural SVMs and its applications in computer vision.” 2014. Web. 23 Feb 2020.

Vancouver:

旷章辉; Kuang Z. Learning structural SVMs and its applications in computer vision. [Internet] [Doctoral dissertation]. University of Hong Kong; 2014. [cited 2020 Feb 23]. Available from: Kuang, Z. [旷章辉]. (2014). Learning structural SVMs and its applications in computer vision. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5223970 ; http://dx.doi.org/10.5353/th_b5223970 ; http://hdl.handle.net/10722/206663.

Council of Science Editors:

旷章辉; Kuang Z. Learning structural SVMs and its applications in computer vision. [Doctoral Dissertation]. University of Hong Kong; 2014. Available from: Kuang, Z. [旷章辉]. (2014). Learning structural SVMs and its applications in computer vision. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5223970 ; http://dx.doi.org/10.5353/th_b5223970 ; http://hdl.handle.net/10722/206663


Virginia Commonwealth University

2. Hess, Eric. Ramp Loss SVM with L1-Norm Regularizaion.

Degree: MS, Mathematical Sciences, 2014, Virginia Commonwealth University

  The Support Vector Machine (SVM) classification method has recently gained popularity due to the ease of implementing non-linear separating surfaces. SVM is an optimization… (more)

Subjects/Keywords: Classification; Support Vector Machines; Analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hess, E. (2014). Ramp Loss SVM with L1-Norm Regularizaion. (Thesis). Virginia Commonwealth University. Retrieved from https://doi.org/10.25772/X3KY-Q384 ; https://scholarscompass.vcu.edu/etd/3538

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hess, Eric. “Ramp Loss SVM with L1-Norm Regularizaion.” 2014. Thesis, Virginia Commonwealth University. Accessed February 23, 2020. https://doi.org/10.25772/X3KY-Q384 ; https://scholarscompass.vcu.edu/etd/3538.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hess, Eric. “Ramp Loss SVM with L1-Norm Regularizaion.” 2014. Web. 23 Feb 2020.

Vancouver:

Hess E. Ramp Loss SVM with L1-Norm Regularizaion. [Internet] [Thesis]. Virginia Commonwealth University; 2014. [cited 2020 Feb 23]. Available from: https://doi.org/10.25772/X3KY-Q384 ; https://scholarscompass.vcu.edu/etd/3538.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hess E. Ramp Loss SVM with L1-Norm Regularizaion. [Thesis]. Virginia Commonwealth University; 2014. Available from: https://doi.org/10.25772/X3KY-Q384 ; https://scholarscompass.vcu.edu/etd/3538

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Colorado State University

3. Carr, Brittany M. Generic support vector machines and Radon's theorem.

Degree: MS(M.S.), Mathematics, 2019, Colorado State University

 A support vector machine, (SVM), is an algorithm which finds a hyperplane that optimally separates labeled data points in Rn into positive and negative classes.… (more)

Subjects/Keywords: support vector machines; Radon's theorem

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Carr, B. M. (2019). Generic support vector machines and Radon's theorem. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/197262

Chicago Manual of Style (16th Edition):

Carr, Brittany M. “Generic support vector machines and Radon's theorem.” 2019. Masters Thesis, Colorado State University. Accessed February 23, 2020. http://hdl.handle.net/10217/197262.

MLA Handbook (7th Edition):

Carr, Brittany M. “Generic support vector machines and Radon's theorem.” 2019. Web. 23 Feb 2020.

Vancouver:

Carr BM. Generic support vector machines and Radon's theorem. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10217/197262.

Council of Science Editors:

Carr BM. Generic support vector machines and Radon's theorem. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/197262


Université de Sherbrooke

4. D'Orangeville, Vincent. Analyse automatique de données par Support Vector Machines non supervisés .

Degree: 2012, Université de Sherbrooke

 Cette dissertation présente un ensemble d'algorithmes visant à en permettre un usage rapide, robuste et automatique des « Support Vector Machines » (SVM) non supervisés… (more)

Subjects/Keywords: Support Vector Machines; Support Vector Clustering; Support Vector Domain Description

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

D'Orangeville, V. (2012). Analyse automatique de données par Support Vector Machines non supervisés . (Doctoral Dissertation). Université de Sherbrooke. Retrieved from http://hdl.handle.net/11143/6678

Chicago Manual of Style (16th Edition):

D'Orangeville, Vincent. “Analyse automatique de données par Support Vector Machines non supervisés .” 2012. Doctoral Dissertation, Université de Sherbrooke. Accessed February 23, 2020. http://hdl.handle.net/11143/6678.

MLA Handbook (7th Edition):

D'Orangeville, Vincent. “Analyse automatique de données par Support Vector Machines non supervisés .” 2012. Web. 23 Feb 2020.

Vancouver:

D'Orangeville V. Analyse automatique de données par Support Vector Machines non supervisés . [Internet] [Doctoral dissertation]. Université de Sherbrooke; 2012. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/11143/6678.

Council of Science Editors:

D'Orangeville V. Analyse automatique de données par Support Vector Machines non supervisés . [Doctoral Dissertation]. Université de Sherbrooke; 2012. Available from: http://hdl.handle.net/11143/6678


University of Alberta

5. Miao, Chuxiong. A support vector machine model for pipe crack size classification.

Degree: MS, Department of Mechanical Engineering, 2009, University of Alberta

 Classifying pipe cracks by size from their pulse-echo ultrasonic signal is difficult but highly significant for the defect evaluation required in pipe testing and maintenance… (more)

Subjects/Keywords: KFD; support vector machines; data dependent kernel

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Miao, C. (2009). A support vector machine model for pipe crack size classification. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/sb397995n

Chicago Manual of Style (16th Edition):

Miao, Chuxiong. “A support vector machine model for pipe crack size classification.” 2009. Masters Thesis, University of Alberta. Accessed February 23, 2020. https://era.library.ualberta.ca/files/sb397995n.

MLA Handbook (7th Edition):

Miao, Chuxiong. “A support vector machine model for pipe crack size classification.” 2009. Web. 23 Feb 2020.

Vancouver:

Miao C. A support vector machine model for pipe crack size classification. [Internet] [Masters thesis]. University of Alberta; 2009. [cited 2020 Feb 23]. Available from: https://era.library.ualberta.ca/files/sb397995n.

Council of Science Editors:

Miao C. A support vector machine model for pipe crack size classification. [Masters Thesis]. University of Alberta; 2009. Available from: https://era.library.ualberta.ca/files/sb397995n


University of New Mexico

6. Atwood, Thomas. RF channel characterization for cognitive radio using support vector machines.

Degree: Electrical and Computer Engineering, 2010, University of New Mexico

 Cognitive Radio promises to revolutionize the ways in which a user interfaces with a communications device. In addition to connecting a user with the rest… (more)

Subjects/Keywords: Cognitive radio networks.; Support vector machines.

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Atwood, T. (2010). RF channel characterization for cognitive radio using support vector machines. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/10298

Chicago Manual of Style (16th Edition):

Atwood, Thomas. “RF channel characterization for cognitive radio using support vector machines.” 2010. Doctoral Dissertation, University of New Mexico. Accessed February 23, 2020. http://hdl.handle.net/1928/10298.

MLA Handbook (7th Edition):

Atwood, Thomas. “RF channel characterization for cognitive radio using support vector machines.” 2010. Web. 23 Feb 2020.

Vancouver:

Atwood T. RF channel characterization for cognitive radio using support vector machines. [Internet] [Doctoral dissertation]. University of New Mexico; 2010. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/1928/10298.

Council of Science Editors:

Atwood T. RF channel characterization for cognitive radio using support vector machines. [Doctoral Dissertation]. University of New Mexico; 2010. Available from: http://hdl.handle.net/1928/10298


Cornell University

7. Yu, Chun Nam. Improved Learning Of Structural Support Vector Machines: Training With Latent Variables And Nonlinear Kernels .

Degree: 2011, Cornell University

 Structured output prediction in machine learning is the study of learning to predict complex objects consisting of many correlated parts, such as sequences, trees, or… (more)

Subjects/Keywords: Structured Output Learning; Support Vector Machines; Kernels

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yu, C. N. (2011). Improved Learning Of Structural Support Vector Machines: Training With Latent Variables And Nonlinear Kernels . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/33469

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yu, Chun Nam. “Improved Learning Of Structural Support Vector Machines: Training With Latent Variables And Nonlinear Kernels .” 2011. Thesis, Cornell University. Accessed February 23, 2020. http://hdl.handle.net/1813/33469.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yu, Chun Nam. “Improved Learning Of Structural Support Vector Machines: Training With Latent Variables And Nonlinear Kernels .” 2011. Web. 23 Feb 2020.

Vancouver:

Yu CN. Improved Learning Of Structural Support Vector Machines: Training With Latent Variables And Nonlinear Kernels . [Internet] [Thesis]. Cornell University; 2011. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/1813/33469.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yu CN. Improved Learning Of Structural Support Vector Machines: Training With Latent Variables And Nonlinear Kernels . [Thesis]. Cornell University; 2011. Available from: http://hdl.handle.net/1813/33469

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of North Texas

8. Giritharan, Balathasan. Incremental Learning with Large Datasets.

Degree: 2012, University of North Texas

 This dissertation focuses on the novel learning strategy based on geometric support vector machines to address the difficulties of processing immense data set. Support vector(more)

Subjects/Keywords: Support vector machines; incremental learning; large datasets

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Giritharan, B. (2012). Incremental Learning with Large Datasets. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc149595/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Giritharan, Balathasan. “Incremental Learning with Large Datasets.” 2012. Thesis, University of North Texas. Accessed February 23, 2020. https://digital.library.unt.edu/ark:/67531/metadc149595/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Giritharan, Balathasan. “Incremental Learning with Large Datasets.” 2012. Web. 23 Feb 2020.

Vancouver:

Giritharan B. Incremental Learning with Large Datasets. [Internet] [Thesis]. University of North Texas; 2012. [cited 2020 Feb 23]. Available from: https://digital.library.unt.edu/ark:/67531/metadc149595/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Giritharan B. Incremental Learning with Large Datasets. [Thesis]. University of North Texas; 2012. Available from: https://digital.library.unt.edu/ark:/67531/metadc149595/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of New South Wales

9. Sarker, Chandrama. Mixed Pixel Analysis and Assessment for Flood Mapping.

Degree: Engineering & Information Technology, 2014, University of New South Wales

 The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered… (more)

Subjects/Keywords: Linear Spectral Unmixing; Support Vector Machines; Flood Mapping; Mixed Pixel; Extended Support Vector Machines

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sarker, C. (2014). Mixed Pixel Analysis and Assessment for Flood Mapping. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53923 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12633/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Sarker, Chandrama. “Mixed Pixel Analysis and Assessment for Flood Mapping.” 2014. Masters Thesis, University of New South Wales. Accessed February 23, 2020. http://handle.unsw.edu.au/1959.4/53923 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12633/SOURCE02?view=true.

MLA Handbook (7th Edition):

Sarker, Chandrama. “Mixed Pixel Analysis and Assessment for Flood Mapping.” 2014. Web. 23 Feb 2020.

Vancouver:

Sarker C. Mixed Pixel Analysis and Assessment for Flood Mapping. [Internet] [Masters thesis]. University of New South Wales; 2014. [cited 2020 Feb 23]. Available from: http://handle.unsw.edu.au/1959.4/53923 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12633/SOURCE02?view=true.

Council of Science Editors:

Sarker C. Mixed Pixel Analysis and Assessment for Flood Mapping. [Masters Thesis]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/53923 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12633/SOURCE02?view=true


Uppsala University

10. Hedlund, Henrik. Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem.

Degree: Linguistics and Philology, 2016, Uppsala University

  The study explores binary classification with Support Vector Machines as means to predict a satisfaction score based on customer surveys in the customer supportdomain.… (more)

Subjects/Keywords: Binary Classification; Customer Support; Chat; Opinion Mining; Support Vector Machines

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hedlund, H. (2016). Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-300165

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hedlund, Henrik. “Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem.” 2016. Thesis, Uppsala University. Accessed February 23, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-300165.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hedlund, Henrik. “Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem.” 2016. Web. 23 Feb 2020.

Vancouver:

Hedlund H. Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem. [Internet] [Thesis]. Uppsala University; 2016. [cited 2020 Feb 23]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-300165.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hedlund H. Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem. [Thesis]. Uppsala University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-300165

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

11. Taylor, Aimee Elizabeth. Statistical enhancement of support vector machines.

Degree: PhD, Statistics, 2009, Oregon State University

Support Vector Machines (SVM) and Random Forests (RF) have consistently outperformed other machine learning algorithms on a variety of problems. SVM can be used for… (more)

Subjects/Keywords: Support Vector Machines; Support vector machines

…3 2.1 Support Vector Machines ….... 3 2.2 SVM Classification… …Support Vector Machine 1 Introduction Machine learning is concerned with training machines to… …x5B;0, ). 2.1 Support Vector Machines Support Vector Machines are based on statistical… …are the Support Vector Machine algorithm (SVM) (Vapnik, 1998) and Random… …boundary. This simplest type of SVM is called a linear support vector machine (LSVM)… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Taylor, A. E. (2009). Statistical enhancement of support vector machines. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/11188

Chicago Manual of Style (16th Edition):

Taylor, Aimee Elizabeth. “Statistical enhancement of support vector machines.” 2009. Doctoral Dissertation, Oregon State University. Accessed February 23, 2020. http://hdl.handle.net/1957/11188.

MLA Handbook (7th Edition):

Taylor, Aimee Elizabeth. “Statistical enhancement of support vector machines.” 2009. Web. 23 Feb 2020.

Vancouver:

Taylor AE. Statistical enhancement of support vector machines. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/1957/11188.

Council of Science Editors:

Taylor AE. Statistical enhancement of support vector machines. [Doctoral Dissertation]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/11188


University of Saskatchewan

12. Azizi, Mahsa 1992-. An Efficient Remand Risk Assessment Tool based on Machine Learning Techniques.

Degree: 2019, University of Saskatchewan

 The criminal justice system in Saskatchewan is challenged by the large population of people who are charged with committing crimes and are waiting to be… (more)

Subjects/Keywords: Machine Learning; Random Forests; Support Vector Machines; Naive Bayes; Extreme Learning Machines; Decision Trees

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Azizi, M. 1. (2019). An Efficient Remand Risk Assessment Tool based on Machine Learning Techniques. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/12421

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Azizi, Mahsa 1992-. “An Efficient Remand Risk Assessment Tool based on Machine Learning Techniques.” 2019. Thesis, University of Saskatchewan. Accessed February 23, 2020. http://hdl.handle.net/10388/12421.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Azizi, Mahsa 1992-. “An Efficient Remand Risk Assessment Tool based on Machine Learning Techniques.” 2019. Web. 23 Feb 2020.

Vancouver:

Azizi M1. An Efficient Remand Risk Assessment Tool based on Machine Learning Techniques. [Internet] [Thesis]. University of Saskatchewan; 2019. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10388/12421.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Azizi M1. An Efficient Remand Risk Assessment Tool based on Machine Learning Techniques. [Thesis]. University of Saskatchewan; 2019. Available from: http://hdl.handle.net/10388/12421

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Alberta

13. Wang, Baoliang. Automatic Animal Species Identification Based on Camera Trapping Data.

Degree: MS, Department of Computing Science, 2014, University of Alberta

 The classification of animal images based on camera trapping data is an important and challenging task in the domains of computer vision, machine learning and… (more)

Subjects/Keywords: Animal Species Identification; Support Vector Machines; Average Pooling; Fisher Vector; Camera Trapping; Gaussian Mixture Model

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, B. (2014). Automatic Animal Species Identification Based on Camera Trapping Data. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/ms35t9138

Chicago Manual of Style (16th Edition):

Wang, Baoliang. “Automatic Animal Species Identification Based on Camera Trapping Data.” 2014. Masters Thesis, University of Alberta. Accessed February 23, 2020. https://era.library.ualberta.ca/files/ms35t9138.

MLA Handbook (7th Edition):

Wang, Baoliang. “Automatic Animal Species Identification Based on Camera Trapping Data.” 2014. Web. 23 Feb 2020.

Vancouver:

Wang B. Automatic Animal Species Identification Based on Camera Trapping Data. [Internet] [Masters thesis]. University of Alberta; 2014. [cited 2020 Feb 23]. Available from: https://era.library.ualberta.ca/files/ms35t9138.

Council of Science Editors:

Wang B. Automatic Animal Species Identification Based on Camera Trapping Data. [Masters Thesis]. University of Alberta; 2014. Available from: https://era.library.ualberta.ca/files/ms35t9138


Texas A&M University

14. Narayana, Sushirdeep. Affect Recognition Using Electroencephalography Features.

Degree: 2017, Texas A&M University

 Affect is the psychological display of emotion often described with three principal dimensions: 1) valence 2) arousal and 3) dominance. This thesis work explores the… (more)

Subjects/Keywords: affect; electroencephalography; machine learning; Support Vector Machines; feature selection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Narayana, S. (2017). Affect Recognition Using Electroencephalography Features. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161603

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Narayana, Sushirdeep. “Affect Recognition Using Electroencephalography Features.” 2017. Thesis, Texas A&M University. Accessed February 23, 2020. http://hdl.handle.net/1969.1/161603.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Narayana, Sushirdeep. “Affect Recognition Using Electroencephalography Features.” 2017. Web. 23 Feb 2020.

Vancouver:

Narayana S. Affect Recognition Using Electroencephalography Features. [Internet] [Thesis]. Texas A&M University; 2017. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/1969.1/161603.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Narayana S. Affect Recognition Using Electroencephalography Features. [Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161603

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

15. Sita Mahalakshmi, T. Some studies on recognition of handwritten Telugu characters; -.

Degree: Computer Engineering, 2011, Acharya Nagarjuna University

Computers are all pervasive essentialities in today s world and technologies that improve our interactions with them are growing at a never before rate. One… (more)

Subjects/Keywords: Computer Science; Neural Networks; Support Vector Machines; Kernel Trick

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sita Mahalakshmi, T. (2011). Some studies on recognition of handwritten Telugu characters; -. (Thesis). Acharya Nagarjuna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/10438

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sita Mahalakshmi, T. “Some studies on recognition of handwritten Telugu characters; -.” 2011. Thesis, Acharya Nagarjuna University. Accessed February 23, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/10438.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sita Mahalakshmi, T. “Some studies on recognition of handwritten Telugu characters; -.” 2011. Web. 23 Feb 2020.

Vancouver:

Sita Mahalakshmi T. Some studies on recognition of handwritten Telugu characters; -. [Internet] [Thesis]. Acharya Nagarjuna University; 2011. [cited 2020 Feb 23]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10438.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sita Mahalakshmi T. Some studies on recognition of handwritten Telugu characters; -. [Thesis]. Acharya Nagarjuna University; 2011. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/10438

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Missouri – Columbia

16. Liu, Yang (Engineer). People re-identification over non-overlapping camera views.

Degree: 2013, University of Missouri – Columbia

 [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Person re-identification is a computer vision task of recognizing an individual from similar background across… (more)

Subjects/Keywords: Pattern recognition systems.; Computer vision.; Support vector machines.

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Liu, Y. (. (2013). People re-identification over non-overlapping camera views. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/43678

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Liu, Yang (Engineer). “People re-identification over non-overlapping camera views.” 2013. Thesis, University of Missouri – Columbia. Accessed February 23, 2020. http://hdl.handle.net/10355/43678.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Liu, Yang (Engineer). “People re-identification over non-overlapping camera views.” 2013. Web. 23 Feb 2020.

Vancouver:

Liu Y(. People re-identification over non-overlapping camera views. [Internet] [Thesis]. University of Missouri – Columbia; 2013. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10355/43678.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu Y(. People re-identification over non-overlapping camera views. [Thesis]. University of Missouri – Columbia; 2013. Available from: http://hdl.handle.net/10355/43678

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Rochester Institute of Technology

17. Lai, Di. Independent component analysis (ICA) applied to ultrasound image processing and tissue characterization.

Degree: Chester F. Carlson Center for Imaging Science (COS), 2009, Rochester Institute of Technology

 As a complicated ubiquitous phenomenon encountered in ultrasound imaging, speckle can be treated as either annoying noise that needs to be reduced or the source… (more)

Subjects/Keywords: Independent component analysis; Support vector machines; Tissue characterization; Ultrasound image processing

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lai, D. (2009). Independent component analysis (ICA) applied to ultrasound image processing and tissue characterization. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/2944

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lai, Di. “Independent component analysis (ICA) applied to ultrasound image processing and tissue characterization.” 2009. Thesis, Rochester Institute of Technology. Accessed February 23, 2020. https://scholarworks.rit.edu/theses/2944.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lai, Di. “Independent component analysis (ICA) applied to ultrasound image processing and tissue characterization.” 2009. Web. 23 Feb 2020.

Vancouver:

Lai D. Independent component analysis (ICA) applied to ultrasound image processing and tissue characterization. [Internet] [Thesis]. Rochester Institute of Technology; 2009. [cited 2020 Feb 23]. Available from: https://scholarworks.rit.edu/theses/2944.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lai D. Independent component analysis (ICA) applied to ultrasound image processing and tissue characterization. [Thesis]. Rochester Institute of Technology; 2009. Available from: https://scholarworks.rit.edu/theses/2944

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brunel University

18. Haddi, Emma. Sentiment analysis : text, pre-processing, reader views and cross domains.

Degree: PhD, 2015, Brunel University

 Sentiment analysis has emerged as a field that has attracted a significant amount of attention since it has a wide variety of applications that could… (more)

Subjects/Keywords: 006.3; Movie reviews; Financial news; Support vector machines (SVM)

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Haddi, E. (2015). Sentiment analysis : text, pre-processing, reader views and cross domains. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/11196 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.659238

Chicago Manual of Style (16th Edition):

Haddi, Emma. “Sentiment analysis : text, pre-processing, reader views and cross domains.” 2015. Doctoral Dissertation, Brunel University. Accessed February 23, 2020. http://bura.brunel.ac.uk/handle/2438/11196 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.659238.

MLA Handbook (7th Edition):

Haddi, Emma. “Sentiment analysis : text, pre-processing, reader views and cross domains.” 2015. Web. 23 Feb 2020.

Vancouver:

Haddi E. Sentiment analysis : text, pre-processing, reader views and cross domains. [Internet] [Doctoral dissertation]. Brunel University; 2015. [cited 2020 Feb 23]. Available from: http://bura.brunel.ac.uk/handle/2438/11196 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.659238.

Council of Science Editors:

Haddi E. Sentiment analysis : text, pre-processing, reader views and cross domains. [Doctoral Dissertation]. Brunel University; 2015. Available from: http://bura.brunel.ac.uk/handle/2438/11196 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.659238

19. LINS, Isis Didier. Support vector machines and particle swarm optimization applied to reliability prediction .

Degree: 2009, Universidade Federal de Pernambuco

 Confiabilidade é uma métrica crítica para as organizações, uma vez que ela influencia diretamente seus desempenhos face à concorrência e é essencial para a manutenção… (more)

Subjects/Keywords: Previsão de Confiabilidade; Otimização via Nuvens de Partículas; Support Vector Machines

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

LINS, I. D. (2009). Support vector machines and particle swarm optimization applied to reliability prediction . (Thesis). Universidade Federal de Pernambuco. Retrieved from http://repositorio.ufpe.br/handle/123456789/5996

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

LINS, Isis Didier. “Support vector machines and particle swarm optimization applied to reliability prediction .” 2009. Thesis, Universidade Federal de Pernambuco. Accessed February 23, 2020. http://repositorio.ufpe.br/handle/123456789/5996.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

LINS, Isis Didier. “Support vector machines and particle swarm optimization applied to reliability prediction .” 2009. Web. 23 Feb 2020.

Vancouver:

LINS ID. Support vector machines and particle swarm optimization applied to reliability prediction . [Internet] [Thesis]. Universidade Federal de Pernambuco; 2009. [cited 2020 Feb 23]. Available from: http://repositorio.ufpe.br/handle/123456789/5996.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

LINS ID. Support vector machines and particle swarm optimization applied to reliability prediction . [Thesis]. Universidade Federal de Pernambuco; 2009. Available from: http://repositorio.ufpe.br/handle/123456789/5996

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

20. Nag, Abhikesh. Combined Generative-Discriminative Learning for Object Recognition using Local Image Descriptors.

Degree: MS, Electrical Engineering, 2008, Penn State University

 We present a system for scale and affine invariant recognition of vehicular objects in video sequences. We use local descriptors (SIFT keypoints) from image frames… (more)

Subjects/Keywords: support vector machines; mixture models; SIFT features; generative-discriminative learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Nag, A. (2008). Combined Generative-Discriminative Learning for Object Recognition using Local Image Descriptors. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/8181

Chicago Manual of Style (16th Edition):

Nag, Abhikesh. “Combined Generative-Discriminative Learning for Object Recognition using Local Image Descriptors.” 2008. Masters Thesis, Penn State University. Accessed February 23, 2020. https://etda.libraries.psu.edu/catalog/8181.

MLA Handbook (7th Edition):

Nag, Abhikesh. “Combined Generative-Discriminative Learning for Object Recognition using Local Image Descriptors.” 2008. Web. 23 Feb 2020.

Vancouver:

Nag A. Combined Generative-Discriminative Learning for Object Recognition using Local Image Descriptors. [Internet] [Masters thesis]. Penn State University; 2008. [cited 2020 Feb 23]. Available from: https://etda.libraries.psu.edu/catalog/8181.

Council of Science Editors:

Nag A. Combined Generative-Discriminative Learning for Object Recognition using Local Image Descriptors. [Masters Thesis]. Penn State University; 2008. Available from: https://etda.libraries.psu.edu/catalog/8181

21. Fernandez, Llamosa Michael. Topological Autocorrelations for Prediction of Protein Conformational Stability and Kinase and Protease Inhibitions : トポロジカル自己相関関数を用いた蛋白質の構造安定性とキナーゼ及びプロテアーゼ阻害の予測.

Degree: 博士(情報工学), 2017, Kyushu Institute of Technology / 九州工業大学

The annotation of protein structure and function from sequence and the prediction of compound’s activity from sketch representations are fundamental goals in bio- and chemoinformatics.… (more)

Subjects/Keywords: QSAR; Drug design; Support vector machines; Genetic algorithm; Protein design

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Fernandez, L. M. (2017). Topological Autocorrelations for Prediction of Protein Conformational Stability and Kinase and Protease Inhibitions : トポロジカル自己相関関数を用いた蛋白質の構造安定性とキナーゼ及びプロテアーゼ阻害の予測. (Thesis). Kyushu Institute of Technology / 九州工業大学. Retrieved from http://hdl.handle.net/10228/4874

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Fernandez, Llamosa Michael. “Topological Autocorrelations for Prediction of Protein Conformational Stability and Kinase and Protease Inhibitions : トポロジカル自己相関関数を用いた蛋白質の構造安定性とキナーゼ及びプロテアーゼ阻害の予測.” 2017. Thesis, Kyushu Institute of Technology / 九州工業大学. Accessed February 23, 2020. http://hdl.handle.net/10228/4874.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Fernandez, Llamosa Michael. “Topological Autocorrelations for Prediction of Protein Conformational Stability and Kinase and Protease Inhibitions : トポロジカル自己相関関数を用いた蛋白質の構造安定性とキナーゼ及びプロテアーゼ阻害の予測.” 2017. Web. 23 Feb 2020.

Vancouver:

Fernandez LM. Topological Autocorrelations for Prediction of Protein Conformational Stability and Kinase and Protease Inhibitions : トポロジカル自己相関関数を用いた蛋白質の構造安定性とキナーゼ及びプロテアーゼ阻害の予測. [Internet] [Thesis]. Kyushu Institute of Technology / 九州工業大学; 2017. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10228/4874.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fernandez LM. Topological Autocorrelations for Prediction of Protein Conformational Stability and Kinase and Protease Inhibitions : トポロジカル自己相関関数を用いた蛋白質の構造安定性とキナーゼ及びプロテアーゼ阻害の予測. [Thesis]. Kyushu Institute of Technology / 九州工業大学; 2017. Available from: http://hdl.handle.net/10228/4874

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of the Western Cape

22. Foster, Roland. A comparison of machine learning techniques for hand shape recognition .

Degree: 2015, University of the Western Cape

 There are five fundamental parameters that characterize any sign language gesture. They are hand shape, orientation, motion and location, and facial expressions. The SASL group… (more)

Subjects/Keywords: Optimization; Artificial neural networks; Hand shape recognition; Support vector machines

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Foster, R. (2015). A comparison of machine learning techniques for hand shape recognition . (Thesis). University of the Western Cape. Retrieved from http://hdl.handle.net/11394/4388

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Foster, Roland. “A comparison of machine learning techniques for hand shape recognition .” 2015. Thesis, University of the Western Cape. Accessed February 23, 2020. http://hdl.handle.net/11394/4388.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Foster, Roland. “A comparison of machine learning techniques for hand shape recognition .” 2015. Web. 23 Feb 2020.

Vancouver:

Foster R. A comparison of machine learning techniques for hand shape recognition . [Internet] [Thesis]. University of the Western Cape; 2015. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/11394/4388.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Foster R. A comparison of machine learning techniques for hand shape recognition . [Thesis]. University of the Western Cape; 2015. Available from: http://hdl.handle.net/11394/4388

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Virginia Tech

23. Bhaduri, Sreyoshi. Algorithm to enable intelligent rail break detection.

Degree: MS, Mechanical Engineering, 2013, Virginia Tech

 Wavelet intensity based algorithm developed previously at VirginiaTech has been furthered and paired with an SVM based classifier. The wavelet intensity algorithm acts as a… (more)

Subjects/Keywords: Support Vector Machines; crossing and track safety; rail break detection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bhaduri, S. (2013). Algorithm to enable intelligent rail break detection. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78080

Chicago Manual of Style (16th Edition):

Bhaduri, Sreyoshi. “Algorithm to enable intelligent rail break detection.” 2013. Masters Thesis, Virginia Tech. Accessed February 23, 2020. http://hdl.handle.net/10919/78080.

MLA Handbook (7th Edition):

Bhaduri, Sreyoshi. “Algorithm to enable intelligent rail break detection.” 2013. Web. 23 Feb 2020.

Vancouver:

Bhaduri S. Algorithm to enable intelligent rail break detection. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10919/78080.

Council of Science Editors:

Bhaduri S. Algorithm to enable intelligent rail break detection. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/78080


University of Adelaide

24. Chew, Hong Gunn. Support vector machines with dual error extensions for target detection and object recognition.

Degree: 2013, University of Adelaide

 The Support Vector Machine (SVM) is a binary classification paradigm based on statistical learning. It is an important tool in object detection and pattern recognition,… (more)

Subjects/Keywords: support vector machines; target detection; dual error extensions; nu-svm; multiclass

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chew, H. G. (2013). Support vector machines with dual error extensions for target detection and object recognition. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/96169

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chew, Hong Gunn. “Support vector machines with dual error extensions for target detection and object recognition.” 2013. Thesis, University of Adelaide. Accessed February 23, 2020. http://hdl.handle.net/2440/96169.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chew, Hong Gunn. “Support vector machines with dual error extensions for target detection and object recognition.” 2013. Web. 23 Feb 2020.

Vancouver:

Chew HG. Support vector machines with dual error extensions for target detection and object recognition. [Internet] [Thesis]. University of Adelaide; 2013. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/2440/96169.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chew HG. Support vector machines with dual error extensions for target detection and object recognition. [Thesis]. University of Adelaide; 2013. Available from: http://hdl.handle.net/2440/96169

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


California State University – Channel Islands

25. Mayorga, David M. A Support Vector Machine Approach to Analyzing Aftermarket Ticket Sales .

Degree: 2011, California State University – Channel Islands

Support Vector Machines (SVMs) are used to linearly separate & classify data. If our data is not linearly separable, we use a kernel function to… (more)

Subjects/Keywords: Support vector machines; SVM; SVMs; Ticket; Resale; Analyst; Mathematics thesis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mayorga, D. M. (2011). A Support Vector Machine Approach to Analyzing Aftermarket Ticket Sales . (Thesis). California State University – Channel Islands. Retrieved from http://hdl.handle.net/10139/4993

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mayorga, David M. “A Support Vector Machine Approach to Analyzing Aftermarket Ticket Sales .” 2011. Thesis, California State University – Channel Islands. Accessed February 23, 2020. http://hdl.handle.net/10139/4993.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mayorga, David M. “A Support Vector Machine Approach to Analyzing Aftermarket Ticket Sales .” 2011. Web. 23 Feb 2020.

Vancouver:

Mayorga DM. A Support Vector Machine Approach to Analyzing Aftermarket Ticket Sales . [Internet] [Thesis]. California State University – Channel Islands; 2011. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10139/4993.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mayorga DM. A Support Vector Machine Approach to Analyzing Aftermarket Ticket Sales . [Thesis]. California State University – Channel Islands; 2011. Available from: http://hdl.handle.net/10139/4993

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Melbourne

26. Demyanov, Sergey. Regularization methods for neural networks and related models.

Degree: 2015, University of Melbourne

 Neural networks have become very popular in the last few years. They have demonstrated the best results in areas of image classification, image segmentation, speech… (more)

Subjects/Keywords: regularization; neural networks; model selection; support vector machines; deception detection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Demyanov, S. (2015). Regularization methods for neural networks and related models. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/57198

Chicago Manual of Style (16th Edition):

Demyanov, Sergey. “Regularization methods for neural networks and related models.” 2015. Doctoral Dissertation, University of Melbourne. Accessed February 23, 2020. http://hdl.handle.net/11343/57198.

MLA Handbook (7th Edition):

Demyanov, Sergey. “Regularization methods for neural networks and related models.” 2015. Web. 23 Feb 2020.

Vancouver:

Demyanov S. Regularization methods for neural networks and related models. [Internet] [Doctoral dissertation]. University of Melbourne; 2015. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/11343/57198.

Council of Science Editors:

Demyanov S. Regularization methods for neural networks and related models. [Doctoral Dissertation]. University of Melbourne; 2015. Available from: http://hdl.handle.net/11343/57198


University of South Florida

27. Perumalla, Calvin A. Machine Learning and Adaptive Signal Processing Methods for Electrocardiography Applications.

Degree: 2017, University of South Florida

 This dissertation is directed towards improving the state of art cardiac monitoring methods and automatic diagnosis of cardiac anomalies through modern engineering approaches such as… (more)

Subjects/Keywords: Neural Networks; Support Vector Machines; VCG; WBANs; IoT; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Perumalla, C. A. (2017). Machine Learning and Adaptive Signal Processing Methods for Electrocardiography Applications. (Thesis). University of South Florida. Retrieved from https://scholarcommons.usf.edu/etd/6926

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Perumalla, Calvin A. “Machine Learning and Adaptive Signal Processing Methods for Electrocardiography Applications.” 2017. Thesis, University of South Florida. Accessed February 23, 2020. https://scholarcommons.usf.edu/etd/6926.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Perumalla, Calvin A. “Machine Learning and Adaptive Signal Processing Methods for Electrocardiography Applications.” 2017. Web. 23 Feb 2020.

Vancouver:

Perumalla CA. Machine Learning and Adaptive Signal Processing Methods for Electrocardiography Applications. [Internet] [Thesis]. University of South Florida; 2017. [cited 2020 Feb 23]. Available from: https://scholarcommons.usf.edu/etd/6926.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Perumalla CA. Machine Learning and Adaptive Signal Processing Methods for Electrocardiography Applications. [Thesis]. University of South Florida; 2017. Available from: https://scholarcommons.usf.edu/etd/6926

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Rhodes University

28. Tsilo, Lipontseng Cecilia. Protein secondary structure prediction using neural networks and support vector machines.

Degree: Faculty of Science, Statistics, 2009, Rhodes University

 Predicting the secondary structure of proteins is important in biochemistry because the 3D structure can be determined from the local folds that are found in… (more)

Subjects/Keywords: Neural networks (Computer science); Support vector machines; Proteins  – Structure  – Mathematical models

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tsilo, L. C. (2009). Protein secondary structure prediction using neural networks and support vector machines. (Thesis). Rhodes University. Retrieved from http://hdl.handle.net/10962/d1002809

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tsilo, Lipontseng Cecilia. “Protein secondary structure prediction using neural networks and support vector machines.” 2009. Thesis, Rhodes University. Accessed February 23, 2020. http://hdl.handle.net/10962/d1002809.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tsilo, Lipontseng Cecilia. “Protein secondary structure prediction using neural networks and support vector machines.” 2009. Web. 23 Feb 2020.

Vancouver:

Tsilo LC. Protein secondary structure prediction using neural networks and support vector machines. [Internet] [Thesis]. Rhodes University; 2009. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10962/d1002809.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tsilo LC. Protein secondary structure prediction using neural networks and support vector machines. [Thesis]. Rhodes University; 2009. Available from: http://hdl.handle.net/10962/d1002809

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Wayne State University

29. Albousefi, Alhadi Ali. Vehicle Lane Departure Prediction Based On Support Vector Machines.

Degree: PhD, Electrical and Computer Engineering, 2014, Wayne State University

  Advanced driver assistance systems, such as unintentional lane departure warning systems, have recently drawn much attention and R & D efforts. Such a system… (more)

Subjects/Keywords: Prediction; Support vector machines; Unintentional lane departure; Electrical and Computer Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Albousefi, A. A. (2014). Vehicle Lane Departure Prediction Based On Support Vector Machines. (Doctoral Dissertation). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_dissertations/957

Chicago Manual of Style (16th Edition):

Albousefi, Alhadi Ali. “Vehicle Lane Departure Prediction Based On Support Vector Machines.” 2014. Doctoral Dissertation, Wayne State University. Accessed February 23, 2020. https://digitalcommons.wayne.edu/oa_dissertations/957.

MLA Handbook (7th Edition):

Albousefi, Alhadi Ali. “Vehicle Lane Departure Prediction Based On Support Vector Machines.” 2014. Web. 23 Feb 2020.

Vancouver:

Albousefi AA. Vehicle Lane Departure Prediction Based On Support Vector Machines. [Internet] [Doctoral dissertation]. Wayne State University; 2014. [cited 2020 Feb 23]. Available from: https://digitalcommons.wayne.edu/oa_dissertations/957.

Council of Science Editors:

Albousefi AA. Vehicle Lane Departure Prediction Based On Support Vector Machines. [Doctoral Dissertation]. Wayne State University; 2014. Available from: https://digitalcommons.wayne.edu/oa_dissertations/957


University of Waterloo

30. Rashwan, Abdullah. Automatic Driver Fatigue Monitoring Using Hidden Markov Models and Bayesian Networks.

Degree: 2013, University of Waterloo

 The automotive industry is growing bigger each year. The central concern for any automotive company is driver and passenger safety. Many automotive companies have developed… (more)

Subjects/Keywords: Driver fatigue detection; Hidden Markov Models; Support Vector Machines; Bayesian networks

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rashwan, A. (2013). Automatic Driver Fatigue Monitoring Using Hidden Markov Models and Bayesian Networks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/8082

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rashwan, Abdullah. “Automatic Driver Fatigue Monitoring Using Hidden Markov Models and Bayesian Networks.” 2013. Thesis, University of Waterloo. Accessed February 23, 2020. http://hdl.handle.net/10012/8082.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rashwan, Abdullah. “Automatic Driver Fatigue Monitoring Using Hidden Markov Models and Bayesian Networks.” 2013. Web. 23 Feb 2020.

Vancouver:

Rashwan A. Automatic Driver Fatigue Monitoring Using Hidden Markov Models and Bayesian Networks. [Internet] [Thesis]. University of Waterloo; 2013. [cited 2020 Feb 23]. Available from: http://hdl.handle.net/10012/8082.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rashwan A. Automatic Driver Fatigue Monitoring Using Hidden Markov Models and Bayesian Networks. [Thesis]. University of Waterloo; 2013. Available from: http://hdl.handle.net/10012/8082

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

[1] [2] [3] [4] [5] … [17]

.