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You searched for subject:(Learning object). Showing records 1 – 30 of 365 total matches.

[1] [2] [3] [4] [5] … [13]

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Georgia Tech

1. Humayun, Ahmad. Detection and Incremental Object Learning in Videos.

Degree: PhD, Computer Science, 2018, Georgia Tech

 Unlike state-of-the-art batch machine learning methods, children have a remarkable facility for learning visual representations of objects through a combination of self-directed visual exploration and… (more)

Subjects/Keywords: Video Object Detection; Incremental Learning; Object Proposals

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APA (6th Edition):

Humayun, A. (2018). Detection and Incremental Object Learning in Videos. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61614

Chicago Manual of Style (16th Edition):

Humayun, Ahmad. “Detection and Incremental Object Learning in Videos.” 2018. Doctoral Dissertation, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/61614.

MLA Handbook (7th Edition):

Humayun, Ahmad. “Detection and Incremental Object Learning in Videos.” 2018. Web. 17 Sep 2019.

Vancouver:

Humayun A. Detection and Incremental Object Learning in Videos. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/61614.

Council of Science Editors:

Humayun A. Detection and Incremental Object Learning in Videos. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61614


University of Victoria

2. Hagen, Simen. The influence of real-world object expertise on visual discrimination mechanisms.

Degree: Department of Psychology, 2018, University of Victoria

Object experts quickly and accurately discriminate objects within their domain of expertise. Although expert recognition has been extensively studied both at the behavioral- and neural-levels… (more)

Subjects/Keywords: Expert object recognition; Perceptual learning

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APA (6th Edition):

Hagen, S. (2018). The influence of real-world object expertise on visual discrimination mechanisms. (Thesis). University of Victoria. Retrieved from https://dspace.library.uvic.ca//handle/1828/8942

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):

Hagen, Simen. “The influence of real-world object expertise on visual discrimination mechanisms.” 2018. Thesis, University of Victoria. Accessed September 17, 2019. https://dspace.library.uvic.ca//handle/1828/8942.

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

MLA Handbook (7th Edition):

Hagen, Simen. “The influence of real-world object expertise on visual discrimination mechanisms.” 2018. Web. 17 Sep 2019.

Vancouver:

Hagen S. The influence of real-world object expertise on visual discrimination mechanisms. [Internet] [Thesis]. University of Victoria; 2018. [cited 2019 Sep 17]. Available from: https://dspace.library.uvic.ca//handle/1828/8942.

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

Council of Science Editors:

Hagen S. The influence of real-world object expertise on visual discrimination mechanisms. [Thesis]. University of Victoria; 2018. Available from: https://dspace.library.uvic.ca//handle/1828/8942

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


Virginia Tech

3. Yellapantula, Sudha Ravali. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.

Degree: MS, Electrical and Computer Engineering, 2019, Virginia Tech

 In the thesis, we aimed at building a robust UAV(drone) detection algorithm through which, one drone could detect another drone in flight. Though this was… (more)

Subjects/Keywords: GANs; Deep Learning; Object Detection

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

APA (6th Edition):

Yellapantula, S. R. (2019). Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91460

Chicago Manual of Style (16th Edition):

Yellapantula, Sudha Ravali. “Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.” 2019. Masters Thesis, Virginia Tech. Accessed September 17, 2019. http://hdl.handle.net/10919/91460.

MLA Handbook (7th Edition):

Yellapantula, Sudha Ravali. “Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection.” 2019. Web. 17 Sep 2019.

Vancouver:

Yellapantula SR. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10919/91460.

Council of Science Editors:

Yellapantula SR. Synthesizing Realistic Data for Vision Based Drone-to-Drone Detection. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91460

4. Oliveira Pinheiro, Pedro Henrique. Large-Scale Image Segmentation with Convolutional Networks.

Degree: 2017, EPFL

Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial… (more)

Subjects/Keywords: object recognition; artificial neural networks; deep learning; semantic segmentation; object proposals; object detection; image segmentation.

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APA (6th Edition):

Oliveira Pinheiro, P. H. (2017). Large-Scale Image Segmentation with Convolutional Networks. (Thesis). EPFL. Retrieved from http://infoscience.epfl.ch/record/225546

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):

Oliveira Pinheiro, Pedro Henrique. “Large-Scale Image Segmentation with Convolutional Networks.” 2017. Thesis, EPFL. Accessed September 17, 2019. http://infoscience.epfl.ch/record/225546.

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

MLA Handbook (7th Edition):

Oliveira Pinheiro, Pedro Henrique. “Large-Scale Image Segmentation with Convolutional Networks.” 2017. Web. 17 Sep 2019.

Vancouver:

Oliveira Pinheiro PH. Large-Scale Image Segmentation with Convolutional Networks. [Internet] [Thesis]. EPFL; 2017. [cited 2019 Sep 17]. Available from: http://infoscience.epfl.ch/record/225546.

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

Council of Science Editors:

Oliveira Pinheiro PH. Large-Scale Image Segmentation with Convolutional Networks. [Thesis]. EPFL; 2017. Available from: http://infoscience.epfl.ch/record/225546

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


Linköping University

5. Nyström, Axel. Evaluation of Multiple Object Tracking in Surveillance Video.

Degree: Computer Vision, 2019, Linköping University

  Multiple object tracking is the process of assigning unique and consistent identities to objects throughout a video sequence. A popular approach to multiple object(more)

Subjects/Keywords: Multiple Object Tracking; Tracking-by-Detection; Object Detection; Object Tracking; Deep Learning; Signal Processing; Signalbehandling

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

APA (6th Edition):

Nyström, A. (2019). Evaluation of Multiple Object Tracking in Surveillance Video. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666

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):

Nyström, Axel. “Evaluation of Multiple Object Tracking in Surveillance Video.” 2019. Thesis, Linköping University. Accessed September 17, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.

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

MLA Handbook (7th Edition):

Nyström, Axel. “Evaluation of Multiple Object Tracking in Surveillance Video.” 2019. Web. 17 Sep 2019.

Vancouver:

Nyström A. Evaluation of Multiple Object Tracking in Surveillance Video. [Internet] [Thesis]. Linköping University; 2019. [cited 2019 Sep 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666.

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

Council of Science Editors:

Nyström A. Evaluation of Multiple Object Tracking in Surveillance Video. [Thesis]. Linköping University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157666

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


University of Ottawa

6. Zhao, Yiheng. Towards the Design of Neural Network Framework for Object Recognition and Target Region Refining for Smart Transportation Systems .

Degree: 2018, University of Ottawa

Object recognition systems have significant influences on modern life. Face, iris and finger point recognition applications are commonly applied for the security purposes; ASR (Automatic… (more)

Subjects/Keywords: Convolutional Neural Network; Object Detection; Object Recognition; Machine Learning

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APA (6th Edition):

Zhao, Y. (2018). Towards the Design of Neural Network Framework for Object Recognition and Target Region Refining for Smart Transportation Systems . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/37978

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):

Zhao, Yiheng. “Towards the Design of Neural Network Framework for Object Recognition and Target Region Refining for Smart Transportation Systems .” 2018. Thesis, University of Ottawa. Accessed September 17, 2019. http://hdl.handle.net/10393/37978.

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

MLA Handbook (7th Edition):

Zhao, Yiheng. “Towards the Design of Neural Network Framework for Object Recognition and Target Region Refining for Smart Transportation Systems .” 2018. Web. 17 Sep 2019.

Vancouver:

Zhao Y. Towards the Design of Neural Network Framework for Object Recognition and Target Region Refining for Smart Transportation Systems . [Internet] [Thesis]. University of Ottawa; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10393/37978.

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

Council of Science Editors:

Zhao Y. Towards the Design of Neural Network Framework for Object Recognition and Target Region Refining for Smart Transportation Systems . [Thesis]. University of Ottawa; 2018. Available from: http://hdl.handle.net/10393/37978

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


Georgia Tech

7. Sridhar, Sandhya. Computer vision for driver assistance systems.

Degree: MS, Electrical and Computer Engineering, 2018, Georgia Tech

 The objective of the proposed thesis is to illustrate the training, validation and evaluation of vehicle detection algorithms using computer vision and deep learning methods,… (more)

Subjects/Keywords: Computer vision; Deep learning; Autonomous driving; Object tracking; Object detection

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APA (6th Edition):

Sridhar, S. (2018). Computer vision for driver assistance systems. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59938

Chicago Manual of Style (16th Edition):

Sridhar, Sandhya. “Computer vision for driver assistance systems.” 2018. Masters Thesis, Georgia Tech. Accessed September 17, 2019. http://hdl.handle.net/1853/59938.

MLA Handbook (7th Edition):

Sridhar, Sandhya. “Computer vision for driver assistance systems.” 2018. Web. 17 Sep 2019.

Vancouver:

Sridhar S. Computer vision for driver assistance systems. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1853/59938.

Council of Science Editors:

Sridhar S. Computer vision for driver assistance systems. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59938


University of Manitoba

8. Naha, Shujon. Zero-shot Learning for Visual Recognition Problems.

Degree: Computer Science, 2015, University of Manitoba

 In this thesis we discuss different aspects of zero-shot learning and propose solutions for three challenging visual recognition problems: 1) unknown object recognition from images… (more)

Subjects/Keywords: Zero-shot Learning; Computer Vision; Object Recognition; Action Recognition; Object Segmentation

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APA (6th Edition):

Naha, S. (2015). Zero-shot Learning for Visual Recognition Problems. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/31806

Chicago Manual of Style (16th Edition):

Naha, Shujon. “Zero-shot Learning for Visual Recognition Problems.” 2015. Masters Thesis, University of Manitoba. Accessed September 17, 2019. http://hdl.handle.net/1993/31806.

MLA Handbook (7th Edition):

Naha, Shujon. “Zero-shot Learning for Visual Recognition Problems.” 2015. Web. 17 Sep 2019.

Vancouver:

Naha S. Zero-shot Learning for Visual Recognition Problems. [Internet] [Masters thesis]. University of Manitoba; 2015. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1993/31806.

Council of Science Editors:

Naha S. Zero-shot Learning for Visual Recognition Problems. [Masters Thesis]. University of Manitoba; 2015. Available from: http://hdl.handle.net/1993/31806


University of California – Merced

9. Safar, Simon. Learning shape priors with neural networks.

Degree: Electrical Engineering and Computer Science, 2014, University of California – Merced

 We propose two methods for object segmentation by combining learned shape priors with local features. The first, Max-Margin Boltzmann Machines, learns shapes in an unsupervised… (more)

Subjects/Keywords: Computer science; image; learning; object; segmentation

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APA (6th Edition):

Safar, S. (2014). Learning shape priors with neural networks. (Thesis). University of California – Merced. Retrieved from http://www.escholarship.org/uc/item/709186x7

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):

Safar, Simon. “Learning shape priors with neural networks.” 2014. Thesis, University of California – Merced. Accessed September 17, 2019. http://www.escholarship.org/uc/item/709186x7.

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

MLA Handbook (7th Edition):

Safar, Simon. “Learning shape priors with neural networks.” 2014. Web. 17 Sep 2019.

Vancouver:

Safar S. Learning shape priors with neural networks. [Internet] [Thesis]. University of California – Merced; 2014. [cited 2019 Sep 17]. Available from: http://www.escholarship.org/uc/item/709186x7.

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

Council of Science Editors:

Safar S. Learning shape priors with neural networks. [Thesis]. University of California – Merced; 2014. Available from: http://www.escholarship.org/uc/item/709186x7

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


University of Saskatchewan

10. Liu, Jian. Individualized selection of learning objects.

Degree: 2009, University of Saskatchewan

 Rapidly evolving Internet and web technologies and international efforts on standardization of learning object metadata enable learners in a web-based educational system ubiquitous access to… (more)

Subjects/Keywords: learning object; selection; metadata; Bayesian network

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APA (6th Edition):

Liu, J. (2009). Individualized selection of learning objects. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/etd-05122009-093502

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, Jian. “Individualized selection of learning objects.” 2009. Thesis, University of Saskatchewan. Accessed September 17, 2019. http://hdl.handle.net/10388/etd-05122009-093502.

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

MLA Handbook (7th Edition):

Liu, Jian. “Individualized selection of learning objects.” 2009. Web. 17 Sep 2019.

Vancouver:

Liu J. Individualized selection of learning objects. [Internet] [Thesis]. University of Saskatchewan; 2009. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10388/etd-05122009-093502.

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

Council of Science Editors:

Liu J. Individualized selection of learning objects. [Thesis]. University of Saskatchewan; 2009. Available from: http://hdl.handle.net/10388/etd-05122009-093502

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


Virginia Tech

11. Cogswell, Michael Andrew. Understanding Representations and Reducing their Redundancy in Deep Networks.

Degree: MS, Computer Science, 2016, Virginia Tech

 Neural networks in their modern deep learning incarnation have achieved state of the art performance on a wide variety of tasks and domains. A core… (more)

Subjects/Keywords: Object Recognition; Overfitting; Computer Vision; Machine Learning

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APA (6th Edition):

Cogswell, M. A. (2016). Understanding Representations and Reducing their Redundancy in Deep Networks. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78167

Chicago Manual of Style (16th Edition):

Cogswell, Michael Andrew. “Understanding Representations and Reducing their Redundancy in Deep Networks.” 2016. Masters Thesis, Virginia Tech. Accessed September 17, 2019. http://hdl.handle.net/10919/78167.

MLA Handbook (7th Edition):

Cogswell, Michael Andrew. “Understanding Representations and Reducing their Redundancy in Deep Networks.” 2016. Web. 17 Sep 2019.

Vancouver:

Cogswell MA. Understanding Representations and Reducing their Redundancy in Deep Networks. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10919/78167.

Council of Science Editors:

Cogswell MA. Understanding Representations and Reducing their Redundancy in Deep Networks. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/78167


University of Waterloo

12. Mozifian, Melissa Farinaz. Real-time 3D Object Detection for Autonomous Driving.

Degree: 2018, University of Waterloo

 This thesis focuses on advancing the state-of-the-art 3D object detection and localization in autonomous driving. An autonomous vehicle requires operating within a very unpredictable and… (more)

Subjects/Keywords: Computer Vision; Object Detection; Deep Learning

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APA (6th Edition):

Mozifian, M. F. (2018). Real-time 3D Object Detection for Autonomous Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13267

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):

Mozifian, Melissa Farinaz. “Real-time 3D Object Detection for Autonomous Driving.” 2018. Thesis, University of Waterloo. Accessed September 17, 2019. http://hdl.handle.net/10012/13267.

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

MLA Handbook (7th Edition):

Mozifian, Melissa Farinaz. “Real-time 3D Object Detection for Autonomous Driving.” 2018. Web. 17 Sep 2019.

Vancouver:

Mozifian MF. Real-time 3D Object Detection for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10012/13267.

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

Council of Science Editors:

Mozifian MF. Real-time 3D Object Detection for Autonomous Driving. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13267

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


University of Manitoba

13. Gaudreau, Colin. Fast detection of bees using deep learning and bayesian optimization.

Degree: Electrical and Computer Engineering, 2018, University of Manitoba

 In commercial beekeeping, monitoring the apiaries is difficult as they are often spread over large distances. Building a vision-based hive monitoring system is a promising—albeit… (more)

Subjects/Keywords: Computer vision; Object detection; Machine learning; Bees

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

APA (6th Edition):

Gaudreau, C. (2018). Fast detection of bees using deep learning and bayesian optimization. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/32981

Chicago Manual of Style (16th Edition):

Gaudreau, Colin. “Fast detection of bees using deep learning and bayesian optimization.” 2018. Masters Thesis, University of Manitoba. Accessed September 17, 2019. http://hdl.handle.net/1993/32981.

MLA Handbook (7th Edition):

Gaudreau, Colin. “Fast detection of bees using deep learning and bayesian optimization.” 2018. Web. 17 Sep 2019.

Vancouver:

Gaudreau C. Fast detection of bees using deep learning and bayesian optimization. [Internet] [Masters thesis]. University of Manitoba; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1993/32981.

Council of Science Editors:

Gaudreau C. Fast detection of bees using deep learning and bayesian optimization. [Masters Thesis]. University of Manitoba; 2018. Available from: http://hdl.handle.net/1993/32981


University of Oregon

14. Simpson, Steve. History, Context, and Policies of a Learning Object Repository.

Degree: 2016, University of Oregon

Learning object repositories, a form of digital libraries, are robust systems that provide educators new ways to search for educational resources, collaborate with peers, and… (more)

Subjects/Keywords: Curation; Digital libraries; Learning object; Repository

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

APA (6th Edition):

Simpson, S. (2016). History, Context, and Policies of a Learning Object Repository. (Thesis). University of Oregon. Retrieved from http://hdl.handle.net/1794/20541

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):

Simpson, Steve. “History, Context, and Policies of a Learning Object Repository.” 2016. Thesis, University of Oregon. Accessed September 17, 2019. http://hdl.handle.net/1794/20541.

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

MLA Handbook (7th Edition):

Simpson, Steve. “History, Context, and Policies of a Learning Object Repository.” 2016. Web. 17 Sep 2019.

Vancouver:

Simpson S. History, Context, and Policies of a Learning Object Repository. [Internet] [Thesis]. University of Oregon; 2016. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1794/20541.

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

Council of Science Editors:

Simpson S. History, Context, and Policies of a Learning Object Repository. [Thesis]. University of Oregon; 2016. Available from: http://hdl.handle.net/1794/20541

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


King Abdullah University of Science and Technology

15. Xu, Mengmeng. Object Detection Using Multiple Level Annotations.

Degree: 2019, King Abdullah University of Science and Technology

Object detection is a fundamental problem in computer vision. Impressive results have been achieved on large-scale detection benchmarks by fully-supervised object detection (FSOD) methods. However,… (more)

Subjects/Keywords: Object Detection; Hybrid Supervised Learning; Training Budget

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

APA (6th Edition):

Xu, M. (2019). Object Detection Using Multiple Level Annotations. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/631958

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):

Xu, Mengmeng. “Object Detection Using Multiple Level Annotations.” 2019. Thesis, King Abdullah University of Science and Technology. Accessed September 17, 2019. http://hdl.handle.net/10754/631958.

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

MLA Handbook (7th Edition):

Xu, Mengmeng. “Object Detection Using Multiple Level Annotations.” 2019. Web. 17 Sep 2019.

Vancouver:

Xu M. Object Detection Using Multiple Level Annotations. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2019. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10754/631958.

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

Council of Science Editors:

Xu M. Object Detection Using Multiple Level Annotations. [Thesis]. King Abdullah University of Science and Technology; 2019. Available from: http://hdl.handle.net/10754/631958

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


Queens University

16. Diamond, Jonathan. Sensorimotor Mechanisms Involved in Object Oriented Behaviour .

Degree: Neuroscience Studies, 2014, Queens University

 The manipulation of objects is a hallmark skill in the repertoire of human motor behaviour that involves the grasping, lifting and transporting of objects as… (more)

Subjects/Keywords: Movement Decisions; Motor Learning; Reaching; Object Manipulation

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APA (6th Edition):

Diamond, J. (2014). Sensorimotor Mechanisms Involved in Object Oriented Behaviour . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/12673

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):

Diamond, Jonathan. “Sensorimotor Mechanisms Involved in Object Oriented Behaviour .” 2014. Thesis, Queens University. Accessed September 17, 2019. http://hdl.handle.net/1974/12673.

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

MLA Handbook (7th Edition):

Diamond, Jonathan. “Sensorimotor Mechanisms Involved in Object Oriented Behaviour .” 2014. Web. 17 Sep 2019.

Vancouver:

Diamond J. Sensorimotor Mechanisms Involved in Object Oriented Behaviour . [Internet] [Thesis]. Queens University; 2014. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1974/12673.

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

Council of Science Editors:

Diamond J. Sensorimotor Mechanisms Involved in Object Oriented Behaviour . [Thesis]. Queens University; 2014. Available from: http://hdl.handle.net/1974/12673

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


University of New South Wales

17. Wang, Weihong. A Weakly Supervised Approach for Object Detection.

Degree: Computer Science & Engineering, 2016, University of New South Wales

Object detection in images and videos is an important topic in computer vision. In general, a large number of training samples are required to train… (more)

Subjects/Keywords: Boosting; Weakly supervised learning; Multiple instance learning; Object detection; Online learning

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

APA (6th Edition):

Wang, W. (2016). A Weakly Supervised Approach for Object Detection. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/56619 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41053/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Wang, Weihong. “A Weakly Supervised Approach for Object Detection.” 2016. Doctoral Dissertation, University of New South Wales. Accessed September 17, 2019. http://handle.unsw.edu.au/1959.4/56619 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41053/SOURCE02?view=true.

MLA Handbook (7th Edition):

Wang, Weihong. “A Weakly Supervised Approach for Object Detection.” 2016. Web. 17 Sep 2019.

Vancouver:

Wang W. A Weakly Supervised Approach for Object Detection. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2019 Sep 17]. Available from: http://handle.unsw.edu.au/1959.4/56619 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41053/SOURCE02?view=true.

Council of Science Editors:

Wang W. A Weakly Supervised Approach for Object Detection. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/56619 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:41053/SOURCE02?view=true


University of North Texas

18. Xu, Hong. Factors Affecting Faculty Use Of Learning Object Repositories: An Exploratory Study Of Orange Grove And Wisc-online.

Degree: 2011, University of North Texas

 The purpose of this study was to identify factors that motivate or impede faculty use of learning object repositories (LORs). The unified theory of acceptance… (more)

Subjects/Keywords: Learning object; learning object repository; LOR; Orange Grove; Wisc-Online; faculty; education materials; UTAUT

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

APA (6th Edition):

Xu, H. (2011). Factors Affecting Faculty Use Of Learning Object Repositories: An Exploratory Study Of Orange Grove And Wisc-online. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc103412/

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):

Xu, Hong. “Factors Affecting Faculty Use Of Learning Object Repositories: An Exploratory Study Of Orange Grove And Wisc-online.” 2011. Thesis, University of North Texas. Accessed September 17, 2019. https://digital.library.unt.edu/ark:/67531/metadc103412/.

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

MLA Handbook (7th Edition):

Xu, Hong. “Factors Affecting Faculty Use Of Learning Object Repositories: An Exploratory Study Of Orange Grove And Wisc-online.” 2011. Web. 17 Sep 2019.

Vancouver:

Xu H. Factors Affecting Faculty Use Of Learning Object Repositories: An Exploratory Study Of Orange Grove And Wisc-online. [Internet] [Thesis]. University of North Texas; 2011. [cited 2019 Sep 17]. Available from: https://digital.library.unt.edu/ark:/67531/metadc103412/.

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

Council of Science Editors:

Xu H. Factors Affecting Faculty Use Of Learning Object Repositories: An Exploratory Study Of Orange Grove And Wisc-online. [Thesis]. University of North Texas; 2011. Available from: https://digital.library.unt.edu/ark:/67531/metadc103412/

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


Vilnius University

19. Kubilinskienė, Svetlana. Išplėstas skaitmeninių mokymosi išteklių metaduomenų modelis.

Degree: Dissertation, Informatics Engineering, 2012, Vilnius University

Pagrindinis informacinių technologijų (IT) naudojimo mokymuisi tikslas – didinti mokymosi kokybę ir efektyvumą, lengvinti besimokančiojo ir mokytojo darbą. Galima išskirti dvi IT taikymo ugdymui kryptis:… (more)

Subjects/Keywords: Mokymosi objektas; Mokymosi objekto metaduomenis; Mokymosi objektų metaduomenų saugykla; Metodiniai ištekliai; Mokymosi metodai; Learning object; Learning object metadata; Learning object metadata repository; Methodological learning resources; Learning methods

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

APA (6th Edition):

Kubilinskienė, S. (2012). Išplėstas skaitmeninių mokymosi išteklių metaduomenų modelis. (Doctoral Dissertation). Vilnius University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093814-01973 ;

Chicago Manual of Style (16th Edition):

Kubilinskienė, Svetlana. “Išplėstas skaitmeninių mokymosi išteklių metaduomenų modelis.” 2012. Doctoral Dissertation, Vilnius University. Accessed September 17, 2019. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093814-01973 ;.

MLA Handbook (7th Edition):

Kubilinskienė, Svetlana. “Išplėstas skaitmeninių mokymosi išteklių metaduomenų modelis.” 2012. Web. 17 Sep 2019.

Vancouver:

Kubilinskienė S. Išplėstas skaitmeninių mokymosi išteklių metaduomenų modelis. [Internet] [Doctoral dissertation]. Vilnius University; 2012. [cited 2019 Sep 17]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093814-01973 ;.

Council of Science Editors:

Kubilinskienė S. Išplėstas skaitmeninių mokymosi išteklių metaduomenų modelis. [Doctoral Dissertation]. Vilnius University; 2012. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093814-01973 ;


Vilnius University

20. Kubilinskienė, Svetlana. Extended metadata model for digital learning resources.

Degree: PhD, Informatics Engineering, 2012, Vilnius University

The key aim of using information technology (IT) in learning is to increase the learning quality and efficiency, to facilitate a learner’s and a teacher’s… (more)

Subjects/Keywords: Learning object; Learning object metadata; Learning object metadata repository; Methodological learning resources; Learning methods; Mokymosi objektas; Mokymosi objekto metaduomenis; Mokymosi objektų metaduomenų saugykla; Metodiniai ištekliai; Mokymosi metodai

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

APA (6th Edition):

Kubilinskienė, S. (2012). Extended metadata model for digital learning resources. (Doctoral Dissertation). Vilnius University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093822-17816 ;

Chicago Manual of Style (16th Edition):

Kubilinskienė, Svetlana. “Extended metadata model for digital learning resources.” 2012. Doctoral Dissertation, Vilnius University. Accessed September 17, 2019. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093822-17816 ;.

MLA Handbook (7th Edition):

Kubilinskienė, Svetlana. “Extended metadata model for digital learning resources.” 2012. Web. 17 Sep 2019.

Vancouver:

Kubilinskienė S. Extended metadata model for digital learning resources. [Internet] [Doctoral dissertation]. Vilnius University; 2012. [cited 2019 Sep 17]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093822-17816 ;.

Council of Science Editors:

Kubilinskienė S. Extended metadata model for digital learning resources. [Doctoral Dissertation]. Vilnius University; 2012. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2012~D_20120402_093822-17816 ;


University of Houston

21. Basani, Prashanth Reddy 1995-. Online Multi Object Tracking Using Reinforcement Learning.

Degree: Computer Science, Department of, 2018, University of Houston

 This thesis presents an approach to online learning of Multi-Object Tracking (MOT). It is based on representations from a discriminatively trained Convolutional Neural Network (CNN)… (more)

Subjects/Keywords: Multi-Object Tracking; Deep Reinforcement Learning; Online Learning

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

APA (6th Edition):

Basani, P. R. 1. (2018). Online Multi Object Tracking Using Reinforcement Learning. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3447

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):

Basani, Prashanth Reddy 1995-. “Online Multi Object Tracking Using Reinforcement Learning.” 2018. Thesis, University of Houston. Accessed September 17, 2019. http://hdl.handle.net/10657/3447.

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

MLA Handbook (7th Edition):

Basani, Prashanth Reddy 1995-. “Online Multi Object Tracking Using Reinforcement Learning.” 2018. Web. 17 Sep 2019.

Vancouver:

Basani PR1. Online Multi Object Tracking Using Reinforcement Learning. [Internet] [Thesis]. University of Houston; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10657/3447.

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

Council of Science Editors:

Basani PR1. Online Multi Object Tracking Using Reinforcement Learning. [Thesis]. University of Houston; 2018. Available from: http://hdl.handle.net/10657/3447

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


Wayne State University

22. Mahnaz, Faria. Effective Auto Encoder For Unsupervised Sparse Representation.

Degree: MS, Computer Science, 2015, Wayne State University

  High dimensionality and the sheer size of unlabeled data available today demand new development in unsupervised learning of sparse representation. Despite of recent advances… (more)

Subjects/Keywords: Machine Learning; Object classification; Optimization; Representation learning; Computer Sciences

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

APA (6th Edition):

Mahnaz, F. (2015). Effective Auto Encoder For Unsupervised Sparse Representation. (Masters Thesis). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_theses/427

Chicago Manual of Style (16th Edition):

Mahnaz, Faria. “Effective Auto Encoder For Unsupervised Sparse Representation.” 2015. Masters Thesis, Wayne State University. Accessed September 17, 2019. https://digitalcommons.wayne.edu/oa_theses/427.

MLA Handbook (7th Edition):

Mahnaz, Faria. “Effective Auto Encoder For Unsupervised Sparse Representation.” 2015. Web. 17 Sep 2019.

Vancouver:

Mahnaz F. Effective Auto Encoder For Unsupervised Sparse Representation. [Internet] [Masters thesis]. Wayne State University; 2015. [cited 2019 Sep 17]. Available from: https://digitalcommons.wayne.edu/oa_theses/427.

Council of Science Editors:

Mahnaz F. Effective Auto Encoder For Unsupervised Sparse Representation. [Masters Thesis]. Wayne State University; 2015. Available from: https://digitalcommons.wayne.edu/oa_theses/427

23. Ogier du Terrail, Jean. Réseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne : Deep neural networks for the detection of small vehicles in aerial imagery.

Degree: Docteur es, Informatique, 2018, Normandie

Cette thèse présente une tentative d'approche du problème de la détection et discrimination des petits véhicules dans des images aériennes en vue verticale par l'utilisation… (more)

Subjects/Keywords: Détection d'objets; Statistical Learning; Object-detection; Deep-learning; Computer-vision

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

APA (6th Edition):

Ogier du Terrail, J. (2018). Réseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne : Deep neural networks for the detection of small vehicles in aerial imagery. (Doctoral Dissertation). Normandie. Retrieved from http://www.theses.fr/2018NORMC276

Chicago Manual of Style (16th Edition):

Ogier du Terrail, Jean. “Réseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne : Deep neural networks for the detection of small vehicles in aerial imagery.” 2018. Doctoral Dissertation, Normandie. Accessed September 17, 2019. http://www.theses.fr/2018NORMC276.

MLA Handbook (7th Edition):

Ogier du Terrail, Jean. “Réseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne : Deep neural networks for the detection of small vehicles in aerial imagery.” 2018. Web. 17 Sep 2019.

Vancouver:

Ogier du Terrail J. Réseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne : Deep neural networks for the detection of small vehicles in aerial imagery. [Internet] [Doctoral dissertation]. Normandie; 2018. [cited 2019 Sep 17]. Available from: http://www.theses.fr/2018NORMC276.

Council of Science Editors:

Ogier du Terrail J. Réseaux de neurones convolutionnels profonds pour la détection de petits véhicules en imagerie aérienne : Deep neural networks for the detection of small vehicles in aerial imagery. [Doctoral Dissertation]. Normandie; 2018. Available from: http://www.theses.fr/2018NORMC276


University of Missouri – Columbia

24. Chen, Guang. Object detection with large intra-class variation.

Degree: 2011, University of Missouri – Columbia

 For object detection, the state-of-the-art performance is achieved through supervised learning. The performances of object detectors of this kind are mainly determined by two factors:… (more)

Subjects/Keywords: object detection; classifier cascade; local learning; hybrid learning

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

APA (6th Edition):

Chen, G. (2011). Object detection with large intra-class variation. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/14534

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):

Chen, Guang. “Object detection with large intra-class variation.” 2011. Thesis, University of Missouri – Columbia. Accessed September 17, 2019. http://hdl.handle.net/10355/14534.

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

MLA Handbook (7th Edition):

Chen, Guang. “Object detection with large intra-class variation.” 2011. Web. 17 Sep 2019.

Vancouver:

Chen G. Object detection with large intra-class variation. [Internet] [Thesis]. University of Missouri – Columbia; 2011. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10355/14534.

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

Council of Science Editors:

Chen G. Object detection with large intra-class variation. [Thesis]. University of Missouri – Columbia; 2011. Available from: http://hdl.handle.net/10355/14534

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


University of Edinburgh

25. Allan, Moray. Sprite learning and object category recognition using invariant features.

Degree: 2007, University of Edinburgh

 This thesis explores the use of invariant features for learning sprites from image sequences, and for recognising object categories in images. A popular framework for… (more)

Subjects/Keywords: 006.3; Informatics; Computer Science; machine learning; object recognition; object localisation; image interpretation

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

APA (6th Edition):

Allan, M. (2007). Sprite learning and object category recognition using invariant features. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/2430

Chicago Manual of Style (16th Edition):

Allan, Moray. “Sprite learning and object category recognition using invariant features.” 2007. Doctoral Dissertation, University of Edinburgh. Accessed September 17, 2019. http://hdl.handle.net/1842/2430.

MLA Handbook (7th Edition):

Allan, Moray. “Sprite learning and object category recognition using invariant features.” 2007. Web. 17 Sep 2019.

Vancouver:

Allan M. Sprite learning and object category recognition using invariant features. [Internet] [Doctoral dissertation]. University of Edinburgh; 2007. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/1842/2430.

Council of Science Editors:

Allan M. Sprite learning and object category recognition using invariant features. [Doctoral Dissertation]. University of Edinburgh; 2007. Available from: http://hdl.handle.net/1842/2430


Louisiana State University

26. Erdman, Justin Lee. SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS).

Degree: PhD, Computer Sciences, 2015, Louisiana State University

 This work describes the design and development of an optical, Computer Vision (CV) based sensor for use as a Position Reference System (PRS) in Dynamic… (more)

Subjects/Keywords: TLD; machine learning; object detection; computer vision; dynamic positioning; position reference system; object tracking

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

APA (6th Edition):

Erdman, J. L. (2015). SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS). (Doctoral Dissertation). Louisiana State University. Retrieved from etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208

Chicago Manual of Style (16th Edition):

Erdman, Justin Lee. “SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS).” 2015. Doctoral Dissertation, Louisiana State University. Accessed September 17, 2019. etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208.

MLA Handbook (7th Edition):

Erdman, Justin Lee. “SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS).” 2015. Web. 17 Sep 2019.

Vancouver:

Erdman JL. SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS). [Internet] [Doctoral dissertation]. Louisiana State University; 2015. [cited 2019 Sep 17]. Available from: etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208.

Council of Science Editors:

Erdman JL. SeaVipers - Computer Vision and Inertial Position Reference Sensor System (CVIPRSS). [Doctoral Dissertation]. Louisiana State University; 2015. Available from: etd-06012015-195140 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1208


Universidade do Rio Grande do Sul

27. Canto Filho, Alberto Bastos do. MOTRAC : modelo de trajetórias de aprendizagem conceitual.

Degree: 2015, Universidade do Rio Grande do Sul

O presente trabalho avaliou o uso de Tecnologias de Informação e Comunicação (TICs) com o objetivo de melhorar os processos de ensino e de aprendizagem… (more)

Subjects/Keywords: Informática na educação; Learning objects; Objeto de aprendizagem; Learning trajectories model; Learning object project

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APA (6th Edition):

Canto Filho, A. B. d. (2015). MOTRAC : modelo de trajetórias de aprendizagem conceitual. (Thesis). Universidade do Rio Grande do Sul. Retrieved from http://hdl.handle.net/10183/128889

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):

Canto Filho, Alberto Bastos do. “MOTRAC : modelo de trajetórias de aprendizagem conceitual.” 2015. Thesis, Universidade do Rio Grande do Sul. Accessed September 17, 2019. http://hdl.handle.net/10183/128889.

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

MLA Handbook (7th Edition):

Canto Filho, Alberto Bastos do. “MOTRAC : modelo de trajetórias de aprendizagem conceitual.” 2015. Web. 17 Sep 2019.

Vancouver:

Canto Filho ABd. MOTRAC : modelo de trajetórias de aprendizagem conceitual. [Internet] [Thesis]. Universidade do Rio Grande do Sul; 2015. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10183/128889.

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

Council of Science Editors:

Canto Filho ABd. MOTRAC : modelo de trajetórias de aprendizagem conceitual. [Thesis]. Universidade do Rio Grande do Sul; 2015. Available from: http://hdl.handle.net/10183/128889

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


University of Illinois – Urbana-Champaign

28. Smith, Cybelle Marguerite. Mapping the time-course and content of visual predictions with a novel object-scene associative memory paradigm.

Degree: PhD, Psychology, 2018, University of Illinois – Urbana-Champaign

 In the current thesis, we present a series of three ERP experiments investigating the time-course and nature of contextual facilitation effects in visual object processing.… (more)

Subjects/Keywords: visual object recognition; N300; template matching; contextual learning; paired associate learning; statistical learning

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

APA (6th Edition):

Smith, C. M. (2018). Mapping the time-course and content of visual predictions with a novel object-scene associative memory paradigm. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/102491

Chicago Manual of Style (16th Edition):

Smith, Cybelle Marguerite. “Mapping the time-course and content of visual predictions with a novel object-scene associative memory paradigm.” 2018. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed September 17, 2019. http://hdl.handle.net/2142/102491.

MLA Handbook (7th Edition):

Smith, Cybelle Marguerite. “Mapping the time-course and content of visual predictions with a novel object-scene associative memory paradigm.” 2018. Web. 17 Sep 2019.

Vancouver:

Smith CM. Mapping the time-course and content of visual predictions with a novel object-scene associative memory paradigm. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2018. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/2142/102491.

Council of Science Editors:

Smith CM. Mapping the time-course and content of visual predictions with a novel object-scene associative memory paradigm. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/102491


RMIT University

29. Bui, H. Neural network based image representation for small scale object recognition.

Degree: 2018, RMIT University

Object recognition can be abstractedly viewed as a two-stage process. The features learning stage selects key information that can represent the input image in a… (more)

Subjects/Keywords: Fields of Research; Object recognition; Neural network; Machine learning; Deep learning; Transfer learning; Image processing

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

APA (6th Edition):

Bui, H. (2018). Neural network based image representation for small scale object recognition. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:162586

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):

Bui, H. “Neural network based image representation for small scale object recognition.” 2018. Thesis, RMIT University. Accessed September 17, 2019. http://researchbank.rmit.edu.au/view/rmit:162586.

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

MLA Handbook (7th Edition):

Bui, H. “Neural network based image representation for small scale object recognition.” 2018. Web. 17 Sep 2019.

Vancouver:

Bui H. Neural network based image representation for small scale object recognition. [Internet] [Thesis]. RMIT University; 2018. [cited 2019 Sep 17]. Available from: http://researchbank.rmit.edu.au/view/rmit:162586.

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

Council of Science Editors:

Bui H. Neural network based image representation for small scale object recognition. [Thesis]. RMIT University; 2018. Available from: http://researchbank.rmit.edu.au/view/rmit:162586

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


University of Helsinki

30. Yu, Zhifeng. Expansive learning towards Finnish-Chinese partnership in a cleantech company (2006-2013).

Degree: Institute of Behavioural Sciences; Helsingfors universitet, Beteendevetenskapliga fakulteten, Institutionen för beteendevetenskaper, 2015, University of Helsinki

 Objectives. Cleantech, as an emerging new industry, its development involves the influences from various aspects. As a small to medium-sized cleantech company, the activity in… (more)

Subjects/Keywords: Cleantech; Chinese partnership; expansive learning; activity; object; object oriented network; expansive learning cycle; object formation; network development; expansive learning action; contradiction; expansiveness; zone of proximal development; Adult education; Aikuiskasvatustiede; Vuxenpedagogik; Cleantech; Chinese partnership; expansive learning; activity; object; object oriented network; expansive learning cycle; object formation; network development; expansive learning action; contradiction; expansiveness; zone of proximal development

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

APA (6th Edition):

Yu, Z. (2015). Expansive learning towards Finnish-Chinese partnership in a cleantech company (2006-2013). (Masters Thesis). University of Helsinki. Retrieved from http://hdl.handle.net/10138/157458

Chicago Manual of Style (16th Edition):

Yu, Zhifeng. “Expansive learning towards Finnish-Chinese partnership in a cleantech company (2006-2013).” 2015. Masters Thesis, University of Helsinki. Accessed September 17, 2019. http://hdl.handle.net/10138/157458.

MLA Handbook (7th Edition):

Yu, Zhifeng. “Expansive learning towards Finnish-Chinese partnership in a cleantech company (2006-2013).” 2015. Web. 17 Sep 2019.

Vancouver:

Yu Z. Expansive learning towards Finnish-Chinese partnership in a cleantech company (2006-2013). [Internet] [Masters thesis]. University of Helsinki; 2015. [cited 2019 Sep 17]. Available from: http://hdl.handle.net/10138/157458.

Council of Science Editors:

Yu Z. Expansive learning towards Finnish-Chinese partnership in a cleantech company (2006-2013). [Masters Thesis]. University of Helsinki; 2015. Available from: http://hdl.handle.net/10138/157458

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