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You searched for subject:(image classification). Showing records 1 – 30 of 854 total matches.

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Texas State University – San Marcos

1. Mekala, Sai Swathi. Research of Water Detection in Autonomous Vehicles.

Degree: MS, Engineering, 2019, Texas State University – San Marcos

 An autonomous car is a ground vehicle that navigates without human input. These vehicles are expected to reach $60 billion in sales by 2025. But… (more)

Subjects/Keywords: Image classification

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APA (6th Edition):

Mekala, S. S. (2019). Research of Water Detection in Autonomous Vehicles. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/8998

Chicago Manual of Style (16th Edition):

Mekala, Sai Swathi. “Research of Water Detection in Autonomous Vehicles.” 2019. Masters Thesis, Texas State University – San Marcos. Accessed February 22, 2020. https://digital.library.txstate.edu/handle/10877/8998.

MLA Handbook (7th Edition):

Mekala, Sai Swathi. “Research of Water Detection in Autonomous Vehicles.” 2019. Web. 22 Feb 2020.

Vancouver:

Mekala SS. Research of Water Detection in Autonomous Vehicles. [Internet] [Masters thesis]. Texas State University – San Marcos; 2019. [cited 2020 Feb 22]. Available from: https://digital.library.txstate.edu/handle/10877/8998.

Council of Science Editors:

Mekala SS. Research of Water Detection in Autonomous Vehicles. [Masters Thesis]. Texas State University – San Marcos; 2019. Available from: https://digital.library.txstate.edu/handle/10877/8998


University of Illinois – Urbana-Champaign

2. Xia, Tian. A hybrid approach to problems in image processing.

Degree: PhD, 0112, 2010, University of Illinois – Urbana-Champaign

 Digital image processing generally refers to the use of computer algorithms that deal with operations on or analysis of digital images. It covers a wide… (more)

Subjects/Keywords: computer graphics; image processing; image vectorization; image segmentation; image classification

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APA (6th Edition):

Xia, T. (2010). A hybrid approach to problems in image processing. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/16794

Chicago Manual of Style (16th Edition):

Xia, Tian. “A hybrid approach to problems in image processing.” 2010. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed February 22, 2020. http://hdl.handle.net/2142/16794.

MLA Handbook (7th Edition):

Xia, Tian. “A hybrid approach to problems in image processing.” 2010. Web. 22 Feb 2020.

Vancouver:

Xia T. A hybrid approach to problems in image processing. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2010. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2142/16794.

Council of Science Editors:

Xia T. A hybrid approach to problems in image processing. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/16794


University of Alberta

3. Xu,Bing. Deep Convolutional Networks for Image Classification.

Degree: MS, Department of Computing Science, 2016, University of Alberta

Image classification is an important problem in machine learning. Deep neural networks, particularly deep convolutional networks, have recently contributed great improvements to end-to-end learning quality… (more)

Subjects/Keywords: Deep Networks; Image Classification

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APA (6th Edition):

Xu,Bing. (2016). Deep Convolutional Networks for Image Classification. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cmc87pq29m

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Xu,Bing. “Deep Convolutional Networks for Image Classification.” 2016. Masters Thesis, University of Alberta. Accessed February 22, 2020. https://era.library.ualberta.ca/files/cmc87pq29m.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Xu,Bing. “Deep Convolutional Networks for Image Classification.” 2016. Web. 22 Feb 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Xu,Bing. Deep Convolutional Networks for Image Classification. [Internet] [Masters thesis]. University of Alberta; 2016. [cited 2020 Feb 22]. Available from: https://era.library.ualberta.ca/files/cmc87pq29m.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Xu,Bing. Deep Convolutional Networks for Image Classification. [Masters Thesis]. University of Alberta; 2016. Available from: https://era.library.ualberta.ca/files/cmc87pq29m

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Houston

4. Lin, Hongwei. Red Blood Cell Image Classification Using Model Observers.

Degree: Biomedical Engineering, Department of, 2018, University of Houston

 Healthy red blood cells (RBCs) undergo a gradual morphological transformation during storage. From original healthy discocytes, RBCs gradually lose membrane surface area and cell volume,… (more)

Subjects/Keywords: image classification; model observer

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APA (6th Edition):

Lin, H. (2018). Red Blood Cell Image Classification Using Model Observers. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3513

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):

Lin, Hongwei. “Red Blood Cell Image Classification Using Model Observers.” 2018. Thesis, University of Houston. Accessed February 22, 2020. http://hdl.handle.net/10657/3513.

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

MLA Handbook (7th Edition):

Lin, Hongwei. “Red Blood Cell Image Classification Using Model Observers.” 2018. Web. 22 Feb 2020.

Vancouver:

Lin H. Red Blood Cell Image Classification Using Model Observers. [Internet] [Thesis]. University of Houston; 2018. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/10657/3513.

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

Council of Science Editors:

Lin H. Red Blood Cell Image Classification Using Model Observers. [Thesis]. University of Houston; 2018. Available from: http://hdl.handle.net/10657/3513

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


Kansas State University

5. Dhodda, Pruthvidhar Reddy. Classification of plants in corn fields using machine learning techniques.

Degree: MS, Department of Computer Science, 2018, Kansas State University

 This thesis addresses the tasks of detecting vegetation and classifying plants into target crops and weeds using combinations of machine learning and pattern recognition algorithms… (more)

Subjects/Keywords: Machine learning; Image processing; Classification

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APA (6th Edition):

Dhodda, P. R. (2018). Classification of plants in corn fields using machine learning techniques. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/38890

Chicago Manual of Style (16th Edition):

Dhodda, Pruthvidhar Reddy. “Classification of plants in corn fields using machine learning techniques.” 2018. Masters Thesis, Kansas State University. Accessed February 22, 2020. http://hdl.handle.net/2097/38890.

MLA Handbook (7th Edition):

Dhodda, Pruthvidhar Reddy. “Classification of plants in corn fields using machine learning techniques.” 2018. Web. 22 Feb 2020.

Vancouver:

Dhodda PR. Classification of plants in corn fields using machine learning techniques. [Internet] [Masters thesis]. Kansas State University; 2018. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2097/38890.

Council of Science Editors:

Dhodda PR. Classification of plants in corn fields using machine learning techniques. [Masters Thesis]. Kansas State University; 2018. Available from: http://hdl.handle.net/2097/38890


Université Catholique de Louvain

6. Lebeau, Eric. Study of label errors on a convolutional neural network.

Degree: 2017, Université Catholique de Louvain

Label errors can have a negative impact on the training of a convolutional neural network for image classification. Consequently, the learning of these label errors… (more)

Subjects/Keywords: CNN; Label errors; Image classification; Digits classification

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APA (6th Edition):

Lebeau, E. (2017). Study of label errors on a convolutional neural network. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:13006

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):

Lebeau, Eric. “Study of label errors on a convolutional neural network.” 2017. Thesis, Université Catholique de Louvain. Accessed February 22, 2020. http://hdl.handle.net/2078.1/thesis:13006.

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

MLA Handbook (7th Edition):

Lebeau, Eric. “Study of label errors on a convolutional neural network.” 2017. Web. 22 Feb 2020.

Vancouver:

Lebeau E. Study of label errors on a convolutional neural network. [Internet] [Thesis]. Université Catholique de Louvain; 2017. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2078.1/thesis:13006.

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

Council of Science Editors:

Lebeau E. Study of label errors on a convolutional neural network. [Thesis]. Université Catholique de Louvain; 2017. Available from: http://hdl.handle.net/2078.1/thesis:13006

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


The Ohio State University

7. Ozendi, Mustafa. Viewpoint Independent Image Classification and Retrieval.

Degree: MS, Geodetic Science and Surveying, 2010, The Ohio State University

Image retrieval has applications in different disciplines. For example, there are applications in digital painting catalogues and in security related applications Researchers from both computer… (more)

Subjects/Keywords: Computer Science; image retrieval; image classification; projective invariant; viewpoint independent retrieval; viewpoint independent image classification

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APA (6th Edition):

Ozendi, M. (2010). Viewpoint Independent Image Classification and Retrieval. (Masters Thesis). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1285011830

Chicago Manual of Style (16th Edition):

Ozendi, Mustafa. “Viewpoint Independent Image Classification and Retrieval.” 2010. Masters Thesis, The Ohio State University. Accessed February 22, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1285011830.

MLA Handbook (7th Edition):

Ozendi, Mustafa. “Viewpoint Independent Image Classification and Retrieval.” 2010. Web. 22 Feb 2020.

Vancouver:

Ozendi M. Viewpoint Independent Image Classification and Retrieval. [Internet] [Masters thesis]. The Ohio State University; 2010. [cited 2020 Feb 22]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1285011830.

Council of Science Editors:

Ozendi M. Viewpoint Independent Image Classification and Retrieval. [Masters Thesis]. The Ohio State University; 2010. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1285011830


New Jersey Institute of Technology

8. Banerji, Sugata. Novel color and local image descriptors for content-based image search.

Degree: PhD, Computer Science, 2013, New Jersey Institute of Technology

  Content-based image classification, search and retrieval is a rapidly-expanding research area. With the advent of inexpensive digital cameras, cheap data storage, fast computing speeds… (more)

Subjects/Keywords: Image search; Image classification; Image processing; Color features; Texture features; Scene classification; Computer Sciences

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APA (6th Edition):

Banerji, S. (2013). Novel color and local image descriptors for content-based image search. (Doctoral Dissertation). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/dissertations/358

Chicago Manual of Style (16th Edition):

Banerji, Sugata. “Novel color and local image descriptors for content-based image search.” 2013. Doctoral Dissertation, New Jersey Institute of Technology. Accessed February 22, 2020. https://digitalcommons.njit.edu/dissertations/358.

MLA Handbook (7th Edition):

Banerji, Sugata. “Novel color and local image descriptors for content-based image search.” 2013. Web. 22 Feb 2020.

Vancouver:

Banerji S. Novel color and local image descriptors for content-based image search. [Internet] [Doctoral dissertation]. New Jersey Institute of Technology; 2013. [cited 2020 Feb 22]. Available from: https://digitalcommons.njit.edu/dissertations/358.

Council of Science Editors:

Banerji S. Novel color and local image descriptors for content-based image search. [Doctoral Dissertation]. New Jersey Institute of Technology; 2013. Available from: https://digitalcommons.njit.edu/dissertations/358


Universidade Nova

9. Luu, Thi Phuong Mai. Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam.

Degree: 2009, Universidade Nova

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Wetland is one of the most valuable… (more)

Subjects/Keywords: Image classification; Isodata; Rule based classification; Hybrid classification

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APA (6th Edition):

Luu, T. P. M. (2009). Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam. (Thesis). Universidade Nova. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/2634

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):

Luu, Thi Phuong Mai. “Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam.” 2009. Thesis, Universidade Nova. Accessed February 22, 2020. http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/2634.

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

MLA Handbook (7th Edition):

Luu, Thi Phuong Mai. “Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam.” 2009. Web. 22 Feb 2020.

Vancouver:

Luu TPM. Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam. [Internet] [Thesis]. Universidade Nova; 2009. [cited 2020 Feb 22]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/2634.

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

Council of Science Editors:

Luu TPM. Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam. [Thesis]. Universidade Nova; 2009. Available from: http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/2634

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

10. Nguyen, Vu Lam. Approches complémentaires pour une classification efficace des textures : Complementary Approaches for Efficient Texture Classification.

Degree: Docteur es, STIC (Sciences et Technologies de l'Information et de la Communication) - ED EM2PSI, 2018, Cergy-Pontoise

 Dans cette thèse, nous nous intéressons à la classification des images de textures avec aucune connaissance a priori sur les conditions de numérisation. Cette classification(more)

Subjects/Keywords: Image classification; Texture classification; Représentation; Normalized-Convolution; Feature; Image classification; Feature; Descriptor; Normalized-Convolution; Texture classification

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APA (6th Edition):

Nguyen, V. L. (2018). Approches complémentaires pour une classification efficace des textures : Complementary Approaches for Efficient Texture Classification. (Doctoral Dissertation). Cergy-Pontoise. Retrieved from http://www.theses.fr/2018CERG0974

Chicago Manual of Style (16th Edition):

Nguyen, Vu Lam. “Approches complémentaires pour une classification efficace des textures : Complementary Approaches for Efficient Texture Classification.” 2018. Doctoral Dissertation, Cergy-Pontoise. Accessed February 22, 2020. http://www.theses.fr/2018CERG0974.

MLA Handbook (7th Edition):

Nguyen, Vu Lam. “Approches complémentaires pour une classification efficace des textures : Complementary Approaches for Efficient Texture Classification.” 2018. Web. 22 Feb 2020.

Vancouver:

Nguyen VL. Approches complémentaires pour une classification efficace des textures : Complementary Approaches for Efficient Texture Classification. [Internet] [Doctoral dissertation]. Cergy-Pontoise; 2018. [cited 2020 Feb 22]. Available from: http://www.theses.fr/2018CERG0974.

Council of Science Editors:

Nguyen VL. Approches complémentaires pour une classification efficace des textures : Complementary Approaches for Efficient Texture Classification. [Doctoral Dissertation]. Cergy-Pontoise; 2018. Available from: http://www.theses.fr/2018CERG0974


University of Missouri – Columbia

11. Kanawong, Ratchadaporn. Computer-aided tongue image diagnosis and analysis.

Degree: 2012, University of Missouri – Columbia

 This work focuses on computer-aided tongue image analysis, specifically, as it relates to Traditional Chinese Medicine (TCM). Computerized tongue diagnosis aid medical practitioners capture quantitative… (more)

Subjects/Keywords: diagnostic imaging; image segmentation algorithm; ZHENG classification

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APA (6th Edition):

Kanawong, R. (2012). Computer-aided tongue image diagnosis and analysis. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/35187

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):

Kanawong, Ratchadaporn. “Computer-aided tongue image diagnosis and analysis.” 2012. Thesis, University of Missouri – Columbia. Accessed February 22, 2020. http://hdl.handle.net/10355/35187.

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

MLA Handbook (7th Edition):

Kanawong, Ratchadaporn. “Computer-aided tongue image diagnosis and analysis.” 2012. Web. 22 Feb 2020.

Vancouver:

Kanawong R. Computer-aided tongue image diagnosis and analysis. [Internet] [Thesis]. University of Missouri – Columbia; 2012. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/10355/35187.

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

Council of Science Editors:

Kanawong R. Computer-aided tongue image diagnosis and analysis. [Thesis]. University of Missouri – Columbia; 2012. Available from: http://hdl.handle.net/10355/35187

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


University of Pennsylvania

12. Shin, Daniel B. Novel Statistical Methodologies in Analysis of Position Emission Tomography Data: Applications in Segmentation, Normalization, and Trajectory Modeling.

Degree: 2016, University of Pennsylvania

 Position emission tomography (PET) is a powerful functional imaging modality with wide uses in fields such as oncology, cardiology, and neurology. Motivated by imaging datasets… (more)

Subjects/Keywords: Classification; Image normalization; Nonlinear models; ROC; Biostatistics

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APA (6th Edition):

Shin, D. B. (2016). Novel Statistical Methodologies in Analysis of Position Emission Tomography Data: Applications in Segmentation, Normalization, and Trajectory Modeling. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/2010

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):

Shin, Daniel B. “Novel Statistical Methodologies in Analysis of Position Emission Tomography Data: Applications in Segmentation, Normalization, and Trajectory Modeling.” 2016. Thesis, University of Pennsylvania. Accessed February 22, 2020. https://repository.upenn.edu/edissertations/2010.

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

MLA Handbook (7th Edition):

Shin, Daniel B. “Novel Statistical Methodologies in Analysis of Position Emission Tomography Data: Applications in Segmentation, Normalization, and Trajectory Modeling.” 2016. Web. 22 Feb 2020.

Vancouver:

Shin DB. Novel Statistical Methodologies in Analysis of Position Emission Tomography Data: Applications in Segmentation, Normalization, and Trajectory Modeling. [Internet] [Thesis]. University of Pennsylvania; 2016. [cited 2020 Feb 22]. Available from: https://repository.upenn.edu/edissertations/2010.

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

Council of Science Editors:

Shin DB. Novel Statistical Methodologies in Analysis of Position Emission Tomography Data: Applications in Segmentation, Normalization, and Trajectory Modeling. [Thesis]. University of Pennsylvania; 2016. Available from: https://repository.upenn.edu/edissertations/2010

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


University of Southern California

13. Kim, Eunyoung. Scalable object classification using range images.

Degree: PhD, Computer Science, 2011, University of Southern California

 Object classification using depth images has been actively studied in robotics and computer vision fields to autonomously recognize 3D objects in the scene even under… (more)

Subjects/Keywords: computer vision; object classification; range image

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APA (6th Edition):

Kim, E. (2011). Scalable object classification using range images. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/215990/rec/5683

Chicago Manual of Style (16th Edition):

Kim, Eunyoung. “Scalable object classification using range images.” 2011. Doctoral Dissertation, University of Southern California. Accessed February 22, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/215990/rec/5683.

MLA Handbook (7th Edition):

Kim, Eunyoung. “Scalable object classification using range images.” 2011. Web. 22 Feb 2020.

Vancouver:

Kim E. Scalable object classification using range images. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2020 Feb 22]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/215990/rec/5683.

Council of Science Editors:

Kim E. Scalable object classification using range images. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/215990/rec/5683


Université Catholique de Louvain

14. Antoine, Noé. Segmentation of fingerprint images on a glass plate : a multi-class fern approach.

Degree: 2017, Université Catholique de Louvain

In the scope of a larger work studying the signature electrical signals of particular strains in the fingers, this work addresses the issue of segmenting… (more)

Subjects/Keywords: Fingerprint; Morphology; Ferns; Classification; Segmentation; Image

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APA (6th Edition):

Antoine, N. (2017). Segmentation of fingerprint images on a glass plate : a multi-class fern approach. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/thesis:12936

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):

Antoine, Noé. “Segmentation of fingerprint images on a glass plate : a multi-class fern approach.” 2017. Thesis, Université Catholique de Louvain. Accessed February 22, 2020. http://hdl.handle.net/2078.1/thesis:12936.

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

MLA Handbook (7th Edition):

Antoine, Noé. “Segmentation of fingerprint images on a glass plate : a multi-class fern approach.” 2017. Web. 22 Feb 2020.

Vancouver:

Antoine N. Segmentation of fingerprint images on a glass plate : a multi-class fern approach. [Internet] [Thesis]. Université Catholique de Louvain; 2017. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2078.1/thesis:12936.

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

Council of Science Editors:

Antoine N. Segmentation of fingerprint images on a glass plate : a multi-class fern approach. [Thesis]. Université Catholique de Louvain; 2017. Available from: http://hdl.handle.net/2078.1/thesis:12936

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


Delft University of Technology

15. Nieuwenhuizen, M.C. Virtual reconstruction of hidden paintings based on XRF images:.

Degree: 2010, Delft University of Technology

 This thesis presents a method that uses the chemical information visualized by XRF images to reconstruct hidden compositions: paintings that are buried beneath a surface… (more)

Subjects/Keywords: Painting; XRF; Classification; Image Processing; Reconstruction

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APA (6th Edition):

Nieuwenhuizen, M. C. (2010). Virtual reconstruction of hidden paintings based on XRF images:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:114d170e-f6ec-4551-b406-01f9dd08d18e

Chicago Manual of Style (16th Edition):

Nieuwenhuizen, M C. “Virtual reconstruction of hidden paintings based on XRF images:.” 2010. Masters Thesis, Delft University of Technology. Accessed February 22, 2020. http://resolver.tudelft.nl/uuid:114d170e-f6ec-4551-b406-01f9dd08d18e.

MLA Handbook (7th Edition):

Nieuwenhuizen, M C. “Virtual reconstruction of hidden paintings based on XRF images:.” 2010. Web. 22 Feb 2020.

Vancouver:

Nieuwenhuizen MC. Virtual reconstruction of hidden paintings based on XRF images:. [Internet] [Masters thesis]. Delft University of Technology; 2010. [cited 2020 Feb 22]. Available from: http://resolver.tudelft.nl/uuid:114d170e-f6ec-4551-b406-01f9dd08d18e.

Council of Science Editors:

Nieuwenhuizen MC. Virtual reconstruction of hidden paintings based on XRF images:. [Masters Thesis]. Delft University of Technology; 2010. Available from: http://resolver.tudelft.nl/uuid:114d170e-f6ec-4551-b406-01f9dd08d18e


NSYSU

16. Yang, Cheng-Ju. Image classification via successive core tensor selection procedure.

Degree: Master, Applied Mathematics, 2018, NSYSU

 In the field of artificial intelligence, high-order tensor data have been studied and analyzed, such as the automated optical inspection and MRI. Therefore, tensor decompositions… (more)

Subjects/Keywords: data feature extraction; image classification; tensor decomposition

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

APA (6th Edition):

Yang, C. (2018). Image classification via successive core tensor selection procedure. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922

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):

Yang, Cheng-Ju. “Image classification via successive core tensor selection procedure.” 2018. Thesis, NSYSU. Accessed February 22, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922.

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

MLA Handbook (7th Edition):

Yang, Cheng-Ju. “Image classification via successive core tensor selection procedure.” 2018. Web. 22 Feb 2020.

Vancouver:

Yang C. Image classification via successive core tensor selection procedure. [Internet] [Thesis]. NSYSU; 2018. [cited 2020 Feb 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922.

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

Council of Science Editors:

Yang C. Image classification via successive core tensor selection procedure. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0606118-151922

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


Université Catholique de Louvain

17. Bernard, Guillaume. Incremental organ segmentation with machine learning techniques : application to radiotherapy.

Degree: 2014, Université Catholique de Louvain

Radiotherapy is a cancer treatment modality that can be considered as a ballistic problem where the tumour must be irradiated while sparing the surrounding healthy… (more)

Subjects/Keywords: Radiotherapy; Machine learning; Image segmentation; Incremental classification

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

APA (6th Edition):

Bernard, G. (2014). Incremental organ segmentation with machine learning techniques : application to radiotherapy. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/153438

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):

Bernard, Guillaume. “Incremental organ segmentation with machine learning techniques : application to radiotherapy.” 2014. Thesis, Université Catholique de Louvain. Accessed February 22, 2020. http://hdl.handle.net/2078.1/153438.

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

MLA Handbook (7th Edition):

Bernard, Guillaume. “Incremental organ segmentation with machine learning techniques : application to radiotherapy.” 2014. Web. 22 Feb 2020.

Vancouver:

Bernard G. Incremental organ segmentation with machine learning techniques : application to radiotherapy. [Internet] [Thesis]. Université Catholique de Louvain; 2014. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2078.1/153438.

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

Council of Science Editors:

Bernard G. Incremental organ segmentation with machine learning techniques : application to radiotherapy. [Thesis]. Université Catholique de Louvain; 2014. Available from: http://hdl.handle.net/2078.1/153438

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


University of North Texas

18. Sure, Venkata Leela. Enhanced Approach for the Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using CNN.

Degree: 2019, University of North Texas

 Ulcerative colitis (UC) is a chronic inflammatory disease characterized by periods of relapses and remissions affecting more than 500,000 people in the United States. To… (more)

Subjects/Keywords: Convolutional Neural Network; Medical Image Classification

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

APA (6th Edition):

Sure, V. L. (2019). Enhanced Approach for the Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using CNN. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc1538703/

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):

Sure, Venkata Leela. “Enhanced Approach for the Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using CNN.” 2019. Thesis, University of North Texas. Accessed February 22, 2020. https://digital.library.unt.edu/ark:/67531/metadc1538703/.

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

MLA Handbook (7th Edition):

Sure, Venkata Leela. “Enhanced Approach for the Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using CNN.” 2019. Web. 22 Feb 2020.

Vancouver:

Sure VL. Enhanced Approach for the Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using CNN. [Internet] [Thesis]. University of North Texas; 2019. [cited 2020 Feb 22]. Available from: https://digital.library.unt.edu/ark:/67531/metadc1538703/.

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

Council of Science Editors:

Sure VL. Enhanced Approach for the Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using CNN. [Thesis]. University of North Texas; 2019. Available from: https://digital.library.unt.edu/ark:/67531/metadc1538703/

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


Georgia Tech

19. Prabhu, Viraj Uday. Few-shot learning for dermatological disease diagnosis.

Degree: MS, Computer Science, 2019, Georgia Tech

 In this thesis, we consider the problem of clinical image classification for the purpose of aiding doctors in dermatological disease diagnosis. Diagnosis of dermatological disease… (more)

Subjects/Keywords: Image classification; Low shot learning; Automated diagnosis

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APA (6th Edition):

Prabhu, V. U. (2019). Few-shot learning for dermatological disease diagnosis. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61296

Chicago Manual of Style (16th Edition):

Prabhu, Viraj Uday. “Few-shot learning for dermatological disease diagnosis.” 2019. Masters Thesis, Georgia Tech. Accessed February 22, 2020. http://hdl.handle.net/1853/61296.

MLA Handbook (7th Edition):

Prabhu, Viraj Uday. “Few-shot learning for dermatological disease diagnosis.” 2019. Web. 22 Feb 2020.

Vancouver:

Prabhu VU. Few-shot learning for dermatological disease diagnosis. [Internet] [Masters thesis]. Georgia Tech; 2019. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/1853/61296.

Council of Science Editors:

Prabhu VU. Few-shot learning for dermatological disease diagnosis. [Masters Thesis]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61296


University of Missouri – Columbia

20. Kanawong, Ratchadaporn. Computer-aided tongue image diagnosis and analysis.

Degree: 2012, University of Missouri – Columbia

 This work focuses on computer-aided tongue image analysis, specifically, as it relates to Traditional Chinese Medicine (TCM). Computerized tongue diagnosis aid medical practitioners capture quantitative… (more)

Subjects/Keywords: diagnostic imaging; image segmentation algorithm; ZHENG classification

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

APA (6th Edition):

Kanawong, R. (2012). Computer-aided tongue image diagnosis and analysis. (Thesis). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/35187

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):

Kanawong, Ratchadaporn. “Computer-aided tongue image diagnosis and analysis.” 2012. Thesis, University of Missouri – Columbia. Accessed February 22, 2020. https://doi.org/10.32469/10355/35187.

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

MLA Handbook (7th Edition):

Kanawong, Ratchadaporn. “Computer-aided tongue image diagnosis and analysis.” 2012. Web. 22 Feb 2020.

Vancouver:

Kanawong R. Computer-aided tongue image diagnosis and analysis. [Internet] [Thesis]. University of Missouri – Columbia; 2012. [cited 2020 Feb 22]. Available from: https://doi.org/10.32469/10355/35187.

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

Council of Science Editors:

Kanawong R. Computer-aided tongue image diagnosis and analysis. [Thesis]. University of Missouri – Columbia; 2012. Available from: https://doi.org/10.32469/10355/35187

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

21. Bannour, Hichem. Building and Using Knowledge Models for Semantic Image Annotation : Construction et utilisation de modèles à base de connaissance pour l’annotation sémantique des images.

Degree: Docteur es, Informatique, 2013, Châtenay-Malabry, Ecole centrale de Paris

Cette thèse propose une nouvelle méthodologie pour la construction et l’utilisation de modèles à base de connaissances pour l'annotation automatique d'images. Plus précisément, nous proposons… (more)

Subjects/Keywords: Annotation d'images; Classification hiérarchique d'images; Ontologies multimédia; Image Annotation; Hierarchical Image Classification; Multimedia Ontologies

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

APA (6th Edition):

Bannour, H. (2013). Building and Using Knowledge Models for Semantic Image Annotation : Construction et utilisation de modèles à base de connaissance pour l’annotation sémantique des images. (Doctoral Dissertation). Châtenay-Malabry, Ecole centrale de Paris. Retrieved from http://www.theses.fr/2013ECAP0027

Chicago Manual of Style (16th Edition):

Bannour, Hichem. “Building and Using Knowledge Models for Semantic Image Annotation : Construction et utilisation de modèles à base de connaissance pour l’annotation sémantique des images.” 2013. Doctoral Dissertation, Châtenay-Malabry, Ecole centrale de Paris. Accessed February 22, 2020. http://www.theses.fr/2013ECAP0027.

MLA Handbook (7th Edition):

Bannour, Hichem. “Building and Using Knowledge Models for Semantic Image Annotation : Construction et utilisation de modèles à base de connaissance pour l’annotation sémantique des images.” 2013. Web. 22 Feb 2020.

Vancouver:

Bannour H. Building and Using Knowledge Models for Semantic Image Annotation : Construction et utilisation de modèles à base de connaissance pour l’annotation sémantique des images. [Internet] [Doctoral dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2013. [cited 2020 Feb 22]. Available from: http://www.theses.fr/2013ECAP0027.

Council of Science Editors:

Bannour H. Building and Using Knowledge Models for Semantic Image Annotation : Construction et utilisation de modèles à base de connaissance pour l’annotation sémantique des images. [Doctoral Dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2013. Available from: http://www.theses.fr/2013ECAP0027

22. Znaidia, Amel. Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images.

Degree: Docteur es, Computer science, 2014, Châtenay-Malabry, Ecole centrale de Paris

La présente thèse s’intéresse à l’annotation multimodale d’images dans le contexte des médias sociaux. Notre objectif est de combiner les modalités visuelles et textuelles (tags)… (more)

Subjects/Keywords: Annotation multimodale d’images; Classification supervisée d’images; Imperfections; Multimodal image annotation; Supervised image classification; Tag imperfections

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APA (6th Edition):

Znaidia, A. (2014). Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images. (Doctoral Dissertation). Châtenay-Malabry, Ecole centrale de Paris. Retrieved from http://www.theses.fr/2014ECAP0017

Chicago Manual of Style (16th Edition):

Znaidia, Amel. “Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images.” 2014. Doctoral Dissertation, Châtenay-Malabry, Ecole centrale de Paris. Accessed February 22, 2020. http://www.theses.fr/2014ECAP0017.

MLA Handbook (7th Edition):

Znaidia, Amel. “Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images.” 2014. Web. 22 Feb 2020.

Vancouver:

Znaidia A. Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images. [Internet] [Doctoral dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2014. [cited 2020 Feb 22]. Available from: http://www.theses.fr/2014ECAP0017.

Council of Science Editors:

Znaidia A. Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images. [Doctoral Dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2014. Available from: http://www.theses.fr/2014ECAP0017

23. GONG TIANXIA. Automatic Annotation, Classification and Retrieval of Traumatic Brain Injury CT Images.

Degree: 2011, National University of Singapore

Subjects/Keywords: image annotation; image classification; image retrieval

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APA (6th Edition):

TIANXIA, G. (2011). Automatic Annotation, Classification and Retrieval of Traumatic Brain Injury CT Images. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/30296

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):

TIANXIA, GONG. “Automatic Annotation, Classification and Retrieval of Traumatic Brain Injury CT Images.” 2011. Thesis, National University of Singapore. Accessed February 22, 2020. http://scholarbank.nus.edu.sg/handle/10635/30296.

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

MLA Handbook (7th Edition):

TIANXIA, GONG. “Automatic Annotation, Classification and Retrieval of Traumatic Brain Injury CT Images.” 2011. Web. 22 Feb 2020.

Vancouver:

TIANXIA G. Automatic Annotation, Classification and Retrieval of Traumatic Brain Injury CT Images. [Internet] [Thesis]. National University of Singapore; 2011. [cited 2020 Feb 22]. Available from: http://scholarbank.nus.edu.sg/handle/10635/30296.

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

Council of Science Editors:

TIANXIA G. Automatic Annotation, Classification and Retrieval of Traumatic Brain Injury CT Images. [Thesis]. National University of Singapore; 2011. Available from: http://scholarbank.nus.edu.sg/handle/10635/30296

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


University of Sydney

24. Zhang, Fan. Content-based Medical Image Classification and Retrieval .

Degree: 2016, University of Sydney

 Content-based medical image classification and retrieval are the tasks finding medical images, e.g., of the same category of healthy or abnormal organs, for disease diagnosis… (more)

Subjects/Keywords: Content-based Medical Image Analysis; Medical Image Classification and Retrieval

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

APA (6th Edition):

Zhang, F. (2016). Content-based Medical Image Classification and Retrieval . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/15531

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):

Zhang, Fan. “Content-based Medical Image Classification and Retrieval .” 2016. Thesis, University of Sydney. Accessed February 22, 2020. http://hdl.handle.net/2123/15531.

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

MLA Handbook (7th Edition):

Zhang, Fan. “Content-based Medical Image Classification and Retrieval .” 2016. Web. 22 Feb 2020.

Vancouver:

Zhang F. Content-based Medical Image Classification and Retrieval . [Internet] [Thesis]. University of Sydney; 2016. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2123/15531.

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

Council of Science Editors:

Zhang F. Content-based Medical Image Classification and Retrieval . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/15531

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


Brunel University

25. Kounalakis, Tsampikos. Depth-adaptive methodologies for 3D image caregorization.

Degree: PhD, 2015, Brunel University

Image classification is an active topic of computer vision research. This topic deals with the learning of patterns in order to allow efficient classification of… (more)

Subjects/Keywords: 006.3; 3D imaging; Image classification; Object recognition; Image representation; Deep learning

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APA (6th Edition):

Kounalakis, T. (2015). Depth-adaptive methodologies for 3D image caregorization. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/11531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669124

Chicago Manual of Style (16th Edition):

Kounalakis, Tsampikos. “Depth-adaptive methodologies for 3D image caregorization.” 2015. Doctoral Dissertation, Brunel University. Accessed February 22, 2020. http://bura.brunel.ac.uk/handle/2438/11531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669124.

MLA Handbook (7th Edition):

Kounalakis, Tsampikos. “Depth-adaptive methodologies for 3D image caregorization.” 2015. Web. 22 Feb 2020.

Vancouver:

Kounalakis T. Depth-adaptive methodologies for 3D image caregorization. [Internet] [Doctoral dissertation]. Brunel University; 2015. [cited 2020 Feb 22]. Available from: http://bura.brunel.ac.uk/handle/2438/11531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669124.

Council of Science Editors:

Kounalakis T. Depth-adaptive methodologies for 3D image caregorization. [Doctoral Dissertation]. Brunel University; 2015. Available from: http://bura.brunel.ac.uk/handle/2438/11531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669124


Texas State University – San Marcos

26. Ring, Patrick D. Movement Classification and Analysis from RGB – D Video Data.

Degree: MS, Computer Science, 2019, Texas State University – San Marcos

 The aim of this thesis is to develop and evaluate methods of human movement classification using motion tracking data captured using a RGB-D sensor. As… (more)

Subjects/Keywords: Kinect; Classification; Computer science; Image processing – Digital techniques; Image analysis

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APA (6th Edition):

Ring, P. D. (2019). Movement Classification and Analysis from RGB – D Video Data. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/8325

Chicago Manual of Style (16th Edition):

Ring, Patrick D. “Movement Classification and Analysis from RGB – D Video Data.” 2019. Masters Thesis, Texas State University – San Marcos. Accessed February 22, 2020. https://digital.library.txstate.edu/handle/10877/8325.

MLA Handbook (7th Edition):

Ring, Patrick D. “Movement Classification and Analysis from RGB – D Video Data.” 2019. Web. 22 Feb 2020.

Vancouver:

Ring PD. Movement Classification and Analysis from RGB – D Video Data. [Internet] [Masters thesis]. Texas State University – San Marcos; 2019. [cited 2020 Feb 22]. Available from: https://digital.library.txstate.edu/handle/10877/8325.

Council of Science Editors:

Ring PD. Movement Classification and Analysis from RGB – D Video Data. [Masters Thesis]. Texas State University – San Marcos; 2019. Available from: https://digital.library.txstate.edu/handle/10877/8325


Kansas State University

27. Ghimire, Santosh. Classification of image pixels based on minimum distance and hypothesis testing.

Degree: MS, Department of Statistics, 2011, Kansas State University

 We introduce a new classification method that is applicable to classify image pixels. This work was motivated by the test-based classification (TBC) introduced by Liao… (more)

Subjects/Keywords: Hypothesis testing; minimum distance; image processing; image classification; Statistics (0463)

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

APA (6th Edition):

Ghimire, S. (2011). Classification of image pixels based on minimum distance and hypothesis testing. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/8547

Chicago Manual of Style (16th Edition):

Ghimire, Santosh. “Classification of image pixels based on minimum distance and hypothesis testing.” 2011. Masters Thesis, Kansas State University. Accessed February 22, 2020. http://hdl.handle.net/2097/8547.

MLA Handbook (7th Edition):

Ghimire, Santosh. “Classification of image pixels based on minimum distance and hypothesis testing.” 2011. Web. 22 Feb 2020.

Vancouver:

Ghimire S. Classification of image pixels based on minimum distance and hypothesis testing. [Internet] [Masters thesis]. Kansas State University; 2011. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2097/8547.

Council of Science Editors:

Ghimire S. Classification of image pixels based on minimum distance and hypothesis testing. [Masters Thesis]. Kansas State University; 2011. Available from: http://hdl.handle.net/2097/8547


University of Waterloo

28. Kalra, Shivam. Content-based Image Retrieval of Gigapixel Histopathology Scans: A Comparative Study of Convolution Neural Network, Local Binary Pattern, and Bag of visual Words.

Degree: 2018, University of Waterloo

 The state-of-the-art image analysis algorithms offer a unique opportunity to extract semantically meaningful features from medical images. The advantage of this approach is automation in… (more)

Subjects/Keywords: Content-based Image Retrieval; Digital Pathology; Deep Learning; Image Classification

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APA (6th Edition):

Kalra, S. (2018). Content-based Image Retrieval of Gigapixel Histopathology Scans: A Comparative Study of Convolution Neural Network, Local Binary Pattern, and Bag of visual Words. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13226

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):

Kalra, Shivam. “Content-based Image Retrieval of Gigapixel Histopathology Scans: A Comparative Study of Convolution Neural Network, Local Binary Pattern, and Bag of visual Words.” 2018. Thesis, University of Waterloo. Accessed February 22, 2020. http://hdl.handle.net/10012/13226.

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

MLA Handbook (7th Edition):

Kalra, Shivam. “Content-based Image Retrieval of Gigapixel Histopathology Scans: A Comparative Study of Convolution Neural Network, Local Binary Pattern, and Bag of visual Words.” 2018. Web. 22 Feb 2020.

Vancouver:

Kalra S. Content-based Image Retrieval of Gigapixel Histopathology Scans: A Comparative Study of Convolution Neural Network, Local Binary Pattern, and Bag of visual Words. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/10012/13226.

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

Council of Science Editors:

Kalra S. Content-based Image Retrieval of Gigapixel Histopathology Scans: A Comparative Study of Convolution Neural Network, Local Binary Pattern, and Bag of visual Words. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13226

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


University of North Texas

29. Kumara, Muthukudage Jayantha. Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements.

Degree: 2013, University of North Texas

 The effectiveness of colonoscopy depends on the quality of the inspection of the colon. There was no automated measurement method to evaluate the quality of… (more)

Subjects/Keywords: Image classification; convex hull; objects detection; medical image analysis

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APA (6th Edition):

Kumara, M. J. (2013). Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc283843/

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):

Kumara, Muthukudage Jayantha. “Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements.” 2013. Thesis, University of North Texas. Accessed February 22, 2020. https://digital.library.unt.edu/ark:/67531/metadc283843/.

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

MLA Handbook (7th Edition):

Kumara, Muthukudage Jayantha. “Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements.” 2013. Web. 22 Feb 2020.

Vancouver:

Kumara MJ. Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements. [Internet] [Thesis]. University of North Texas; 2013. [cited 2020 Feb 22]. Available from: https://digital.library.unt.edu/ark:/67531/metadc283843/.

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

Council of Science Editors:

Kumara MJ. Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements. [Thesis]. University of North Texas; 2013. Available from: https://digital.library.unt.edu/ark:/67531/metadc283843/

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


University of Sydney

30. Ahn, Euijoon. Sparse Coding for Medical Image Analysis: Applications to Image Segmentation and Classification .

Degree: 2016, University of Sydney

 Medical imaging is a fundamental and invaluable tool in modern healthcare. The use of medical imaging has greatly increased, and these massive image archives provide… (more)

Subjects/Keywords: Sparsing Coding; Saliency Detection; Convolutional Neural Networks; Image Segmentation; Image Classification

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

APA (6th Edition):

Ahn, E. (2016). Sparse Coding for Medical Image Analysis: Applications to Image Segmentation and Classification . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/14971

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):

Ahn, Euijoon. “Sparse Coding for Medical Image Analysis: Applications to Image Segmentation and Classification .” 2016. Thesis, University of Sydney. Accessed February 22, 2020. http://hdl.handle.net/2123/14971.

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

MLA Handbook (7th Edition):

Ahn, Euijoon. “Sparse Coding for Medical Image Analysis: Applications to Image Segmentation and Classification .” 2016. Web. 22 Feb 2020.

Vancouver:

Ahn E. Sparse Coding for Medical Image Analysis: Applications to Image Segmentation and Classification . [Internet] [Thesis]. University of Sydney; 2016. [cited 2020 Feb 22]. Available from: http://hdl.handle.net/2123/14971.

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

Council of Science Editors:

Ahn E. Sparse Coding for Medical Image Analysis: Applications to Image Segmentation and Classification . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/14971

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

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