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You searched for subject:(Activity recognition). Showing records 1 – 30 of 256 total matches.

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University of Texas – Austin

1. Chen, Chao-Yeh. Learning human activities and poses with interconnected data sources.

Degree: Computer Sciences, 2016, University of Texas – Austin

 Understanding human actions and poses in images or videos is a challenging problem in computer vision. There are different topics related to this problem such… (more)

Subjects/Keywords: Activity recognition; Activity detection

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APA (6th Edition):

Chen, C. (2016). Learning human activities and poses with interconnected data sources. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/40260

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, Chao-Yeh. “Learning human activities and poses with interconnected data sources.” 2016. Thesis, University of Texas – Austin. Accessed April 20, 2019. http://hdl.handle.net/2152/40260.

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

MLA Handbook (7th Edition):

Chen, Chao-Yeh. “Learning human activities and poses with interconnected data sources.” 2016. Web. 20 Apr 2019.

Vancouver:

Chen C. Learning human activities and poses with interconnected data sources. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/2152/40260.

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

Council of Science Editors:

Chen C. Learning human activities and poses with interconnected data sources. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/40260

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


University of Illinois – Urbana-Champaign

2. Arora, Rohan R. Metrics for analytics and visualization of big data with applications to activity recognition.

Degree: MS, Electrical & Computer Engr, 2016, University of Illinois – Urbana-Champaign

Activity recognition systems detect the hidden actions of an agent from sensor measurements made on the agents' actions and the environmental conditions. For such systems,… (more)

Subjects/Keywords: activity; recognition; metrics

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

APA (6th Edition):

Arora, R. R. (2016). Metrics for analytics and visualization of big data with applications to activity recognition. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/90953

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):

Arora, Rohan R. “Metrics for analytics and visualization of big data with applications to activity recognition.” 2016. Thesis, University of Illinois – Urbana-Champaign. Accessed April 20, 2019. http://hdl.handle.net/2142/90953.

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

MLA Handbook (7th Edition):

Arora, Rohan R. “Metrics for analytics and visualization of big data with applications to activity recognition.” 2016. Web. 20 Apr 2019.

Vancouver:

Arora RR. Metrics for analytics and visualization of big data with applications to activity recognition. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/2142/90953.

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

Council of Science Editors:

Arora RR. Metrics for analytics and visualization of big data with applications to activity recognition. [Thesis]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/90953

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


Rochester Institute of Technology

3. Dudley, Michael David. Recognition of human interactions using limb-level feature points.

Degree: Computer Engineering, 2009, Rochester Institute of Technology

 Human activity recognition is an emerging area of research in computer vision with applications in video surveillance, human-computer interaction, robotics, and video annotation. Despite a… (more)

Subjects/Keywords: Activity recognition; Computer vision; Interaction recognition

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

APA (6th Edition):

Dudley, M. D. (2009). Recognition of human interactions using limb-level feature points. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/3223

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):

Dudley, Michael David. “Recognition of human interactions using limb-level feature points.” 2009. Thesis, Rochester Institute of Technology. Accessed April 20, 2019. https://scholarworks.rit.edu/theses/3223.

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

MLA Handbook (7th Edition):

Dudley, Michael David. “Recognition of human interactions using limb-level feature points.” 2009. Web. 20 Apr 2019.

Vancouver:

Dudley MD. Recognition of human interactions using limb-level feature points. [Internet] [Thesis]. Rochester Institute of Technology; 2009. [cited 2019 Apr 20]. Available from: https://scholarworks.rit.edu/theses/3223.

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

Council of Science Editors:

Dudley MD. Recognition of human interactions using limb-level feature points. [Thesis]. Rochester Institute of Technology; 2009. Available from: https://scholarworks.rit.edu/theses/3223

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


Wright State University

4. Angeleas, Anargyros. A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction.

Degree: PhD, Computer Science and Engineering PhD, 2018, Wright State University

 Human Activity Recognition is an actively researched domain for the past fewdecades, and is one of the most eminent applications of today. It is already… (more)

Subjects/Keywords: Computer Science; Human Activity Recognition

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APA (6th Edition):

Angeleas, A. (2018). A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238

Chicago Manual of Style (16th Edition):

Angeleas, Anargyros. “A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction.” 2018. Doctoral Dissertation, Wright State University. Accessed April 20, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238.

MLA Handbook (7th Edition):

Angeleas, Anargyros. “A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction.” 2018. Web. 20 Apr 2019.

Vancouver:

Angeleas A. A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction. [Internet] [Doctoral dissertation]. Wright State University; 2018. [cited 2019 Apr 20]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238.

Council of Science Editors:

Angeleas A. A Multi-Formal Languages Collaborative Scheme for Complex Human Activity Recognition and Behavioral Patterns Extraction. [Doctoral Dissertation]. Wright State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1526984767684238


University of Edinburgh

5. Vafeias, Efstathios. Recognising activities by jointly modelling actions and their effects.

Degree: PhD, 2015, University of Edinburgh

 With the rapid increase in adoption of consumer technologies, including inexpensive but powerful hardware, robotics appears poised at the cusp of widespread deployment in human… (more)

Subjects/Keywords: 006.3; robotic vision; activity recognition

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

APA (6th Edition):

Vafeias, E. (2015). Recognising activities by jointly modelling actions and their effects. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/14182

Chicago Manual of Style (16th Edition):

Vafeias, Efstathios. “Recognising activities by jointly modelling actions and their effects.” 2015. Doctoral Dissertation, University of Edinburgh. Accessed April 20, 2019. http://hdl.handle.net/1842/14182.

MLA Handbook (7th Edition):

Vafeias, Efstathios. “Recognising activities by jointly modelling actions and their effects.” 2015. Web. 20 Apr 2019.

Vancouver:

Vafeias E. Recognising activities by jointly modelling actions and their effects. [Internet] [Doctoral dissertation]. University of Edinburgh; 2015. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/1842/14182.

Council of Science Editors:

Vafeias E. Recognising activities by jointly modelling actions and their effects. [Doctoral Dissertation]. University of Edinburgh; 2015. Available from: http://hdl.handle.net/1842/14182


Hong Kong University of Science and Technology

6. Hu, Hao. Learning-based human activity recognition.

Degree: 2012, Hong Kong University of Science and Technology

 Recognizing human activities has been an extensive and interesting research topic since early 1980s. However, when deploying human activity recognition solutions to the real world,… (more)

Subjects/Keywords: Human activity recognition; Machine learning

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

APA (6th Edition):

Hu, H. (2012). Learning-based human activity recognition. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1206070 ; http://repository.ust.hk/ir/bitstream/1783.1-7811/1/th_redirect.html

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):

Hu, Hao. “Learning-based human activity recognition.” 2012. Thesis, Hong Kong University of Science and Technology. Accessed April 20, 2019. https://doi.org/10.14711/thesis-b1206070 ; http://repository.ust.hk/ir/bitstream/1783.1-7811/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Hu, Hao. “Learning-based human activity recognition.” 2012. Web. 20 Apr 2019.

Vancouver:

Hu H. Learning-based human activity recognition. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2012. [cited 2019 Apr 20]. Available from: https://doi.org/10.14711/thesis-b1206070 ; http://repository.ust.hk/ir/bitstream/1783.1-7811/1/th_redirect.html.

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

Council of Science Editors:

Hu H. Learning-based human activity recognition. [Thesis]. Hong Kong University of Science and Technology; 2012. Available from: https://doi.org/10.14711/thesis-b1206070 ; http://repository.ust.hk/ir/bitstream/1783.1-7811/1/th_redirect.html

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


Western Carolina University

7. Shouse, Kirke. Activity recognition using Grey-Markov model.

Degree: 2011, Western Carolina University

Activity Recognition (AR) is a process of identifying actions and goals of one or more agents of interest. AR techniques have been applied to both… (more)

Subjects/Keywords: Human activity recognition; Markov processes

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APA (6th Edition):

Shouse, K. (2011). Activity recognition using Grey-Markov model. (Masters Thesis). Western Carolina University. Retrieved from http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=9032

Chicago Manual of Style (16th Edition):

Shouse, Kirke. “Activity recognition using Grey-Markov model.” 2011. Masters Thesis, Western Carolina University. Accessed April 20, 2019. http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=9032.

MLA Handbook (7th Edition):

Shouse, Kirke. “Activity recognition using Grey-Markov model.” 2011. Web. 20 Apr 2019.

Vancouver:

Shouse K. Activity recognition using Grey-Markov model. [Internet] [Masters thesis]. Western Carolina University; 2011. [cited 2019 Apr 20]. Available from: http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=9032.

Council of Science Editors:

Shouse K. Activity recognition using Grey-Markov model. [Masters Thesis]. Western Carolina University; 2011. Available from: http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=9032


University of Melbourne

8. Li, Han. Low-cost leaving home activity recognition using mobile sensing.

Degree: 2017, University of Melbourne

 Leaving home activity recognition (LHAR) is essential in context-aware applications. For example, on a rainy day, a smartphone can remind a user to bring an… (more)

Subjects/Keywords: mobile sensing; activity recognition; leaving home activity recognition

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APA (6th Edition):

Li, H. (2017). Low-cost leaving home activity recognition using mobile sensing. (Masters Thesis). University of Melbourne. Retrieved from http://hdl.handle.net/11343/129509

Chicago Manual of Style (16th Edition):

Li, Han. “Low-cost leaving home activity recognition using mobile sensing.” 2017. Masters Thesis, University of Melbourne. Accessed April 20, 2019. http://hdl.handle.net/11343/129509.

MLA Handbook (7th Edition):

Li, Han. “Low-cost leaving home activity recognition using mobile sensing.” 2017. Web. 20 Apr 2019.

Vancouver:

Li H. Low-cost leaving home activity recognition using mobile sensing. [Internet] [Masters thesis]. University of Melbourne; 2017. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/11343/129509.

Council of Science Editors:

Li H. Low-cost leaving home activity recognition using mobile sensing. [Masters Thesis]. University of Melbourne; 2017. Available from: http://hdl.handle.net/11343/129509


University of North Texas

9. Janmohammadi, Siamak. Classifying Pairwise Object Interactions: A Trajectory Analytics Approach.

Degree: 2015, University of North Texas

 We have a huge amount of video data from extensively available surveillance cameras and increasingly growing technology to record the motion of a moving object… (more)

Subjects/Keywords: action recognition; machine learning; trajectory analysis; supervised classification methods; activity recognition; Human activity recognition.; Pattern recognition systems.; Machine learning.; Electronic surveillance.

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

APA (6th Edition):

Janmohammadi, S. (2015). Classifying Pairwise Object Interactions: A Trajectory Analytics Approach. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc801901/

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):

Janmohammadi, Siamak. “Classifying Pairwise Object Interactions: A Trajectory Analytics Approach.” 2015. Thesis, University of North Texas. Accessed April 20, 2019. https://digital.library.unt.edu/ark:/67531/metadc801901/.

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

MLA Handbook (7th Edition):

Janmohammadi, Siamak. “Classifying Pairwise Object Interactions: A Trajectory Analytics Approach.” 2015. Web. 20 Apr 2019.

Vancouver:

Janmohammadi S. Classifying Pairwise Object Interactions: A Trajectory Analytics Approach. [Internet] [Thesis]. University of North Texas; 2015. [cited 2019 Apr 20]. Available from: https://digital.library.unt.edu/ark:/67531/metadc801901/.

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

Council of Science Editors:

Janmohammadi S. Classifying Pairwise Object Interactions: A Trajectory Analytics Approach. [Thesis]. University of North Texas; 2015. Available from: https://digital.library.unt.edu/ark:/67531/metadc801901/

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


University of North Texas

10. Santiteerakul, Wasana. Trajectory Analytics.

Degree: 2015, University of North Texas

 The numerous surveillance videos recorded by a single stationary wide-angle-view camera persuade the use of a moving point as the representation of each small-size object… (more)

Subjects/Keywords: trajectory analytics; action recognition; activity recognition; Pattern recognition systems.; Machine learning.; Human activity recognition.; Electronic surveillance.

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APA (6th Edition):

Santiteerakul, W. (2015). Trajectory Analytics. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc801885/

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):

Santiteerakul, Wasana. “Trajectory Analytics.” 2015. Thesis, University of North Texas. Accessed April 20, 2019. https://digital.library.unt.edu/ark:/67531/metadc801885/.

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

MLA Handbook (7th Edition):

Santiteerakul, Wasana. “Trajectory Analytics.” 2015. Web. 20 Apr 2019.

Vancouver:

Santiteerakul W. Trajectory Analytics. [Internet] [Thesis]. University of North Texas; 2015. [cited 2019 Apr 20]. Available from: https://digital.library.unt.edu/ark:/67531/metadc801885/.

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

Council of Science Editors:

Santiteerakul W. Trajectory Analytics. [Thesis]. University of North Texas; 2015. Available from: https://digital.library.unt.edu/ark:/67531/metadc801885/

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


Nelson Mandela Metropolitan University

11. Amanzi, Richard. A natural user interface architecture using gestures to facilitate the detection of fundamental movement skills.

Degree: Faculty of Science, 2015, Nelson Mandela Metropolitan University

 Fundamental movement skills (FMSs) are considered to be one of the essential phases of motor skill development. The proper development of FMSs allows children to… (more)

Subjects/Keywords: Human activity recognition; Human-computer interaction

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APA (6th Edition):

Amanzi, R. (2015). A natural user interface architecture using gestures to facilitate the detection of fundamental movement skills. (Thesis). Nelson Mandela Metropolitan University. Retrieved from http://hdl.handle.net/10948/6204

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):

Amanzi, Richard. “A natural user interface architecture using gestures to facilitate the detection of fundamental movement skills.” 2015. Thesis, Nelson Mandela Metropolitan University. Accessed April 20, 2019. http://hdl.handle.net/10948/6204.

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

MLA Handbook (7th Edition):

Amanzi, Richard. “A natural user interface architecture using gestures to facilitate the detection of fundamental movement skills.” 2015. Web. 20 Apr 2019.

Vancouver:

Amanzi R. A natural user interface architecture using gestures to facilitate the detection of fundamental movement skills. [Internet] [Thesis]. Nelson Mandela Metropolitan University; 2015. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/10948/6204.

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

Council of Science Editors:

Amanzi R. A natural user interface architecture using gestures to facilitate the detection of fundamental movement skills. [Thesis]. Nelson Mandela Metropolitan University; 2015. Available from: http://hdl.handle.net/10948/6204

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


Massey University

12. Ranhotigmage, Chagitha. Human activities & posture recognition : innovative algorithm for highly accurate detection rate : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Systems Engineering at Massey University, Palmerston North, New Zealand .

Degree: 2013, Massey University

 The main purpose of thesis is to introduce new innovative algorithm for “unintentional fall detection” with 100% accuracy of detecting falls on hard surfaces which… (more)

Subjects/Keywords: Human activity recognition; Mathematical models; Algorithm

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APA (6th Edition):

Ranhotigmage, C. (2013). Human activities & posture recognition : innovative algorithm for highly accurate detection rate : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Systems Engineering at Massey University, Palmerston North, New Zealand . (Thesis). Massey University. Retrieved from http://hdl.handle.net/10179/4339

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):

Ranhotigmage, Chagitha. “Human activities & posture recognition : innovative algorithm for highly accurate detection rate : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Systems Engineering at Massey University, Palmerston North, New Zealand .” 2013. Thesis, Massey University. Accessed April 20, 2019. http://hdl.handle.net/10179/4339.

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

MLA Handbook (7th Edition):

Ranhotigmage, Chagitha. “Human activities & posture recognition : innovative algorithm for highly accurate detection rate : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Systems Engineering at Massey University, Palmerston North, New Zealand .” 2013. Web. 20 Apr 2019.

Vancouver:

Ranhotigmage C. Human activities & posture recognition : innovative algorithm for highly accurate detection rate : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Systems Engineering at Massey University, Palmerston North, New Zealand . [Internet] [Thesis]. Massey University; 2013. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/10179/4339.

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

Council of Science Editors:

Ranhotigmage C. Human activities & posture recognition : innovative algorithm for highly accurate detection rate : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Systems Engineering at Massey University, Palmerston North, New Zealand . [Thesis]. Massey University; 2013. Available from: http://hdl.handle.net/10179/4339

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


Oklahoma State University

13. Kallur, Dharmendra Chandrashekar. Human Localization and Activity Recognition Using Distributed Motion Sensors.

Degree: Electrical Engineering, 2014, Oklahoma State University

 The purpose of this thesis is to localize a human and recognize his/her activities in indoor environments using distributed motion sensors. We propose to use… (more)

Subjects/Keywords: activity recognition; home automation; indoor human localization

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

APA (6th Edition):

Kallur, D. C. (2014). Human Localization and Activity Recognition Using Distributed Motion Sensors. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/14924

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):

Kallur, Dharmendra Chandrashekar. “Human Localization and Activity Recognition Using Distributed Motion Sensors.” 2014. Thesis, Oklahoma State University. Accessed April 20, 2019. http://hdl.handle.net/11244/14924.

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

MLA Handbook (7th Edition):

Kallur, Dharmendra Chandrashekar. “Human Localization and Activity Recognition Using Distributed Motion Sensors.” 2014. Web. 20 Apr 2019.

Vancouver:

Kallur DC. Human Localization and Activity Recognition Using Distributed Motion Sensors. [Internet] [Thesis]. Oklahoma State University; 2014. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/11244/14924.

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

Council of Science Editors:

Kallur DC. Human Localization and Activity Recognition Using Distributed Motion Sensors. [Thesis]. Oklahoma State University; 2014. Available from: http://hdl.handle.net/11244/14924

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


Oklahoma State University

14. Li, Gang. ASCCbot: An Open Mobile Robot Platform.

Degree: School of Electrical & Computer Engineering, 2011, Oklahoma State University

 ASCCbot, an open mobile platform built in ASCC lab, is presented in this thesis. The hardware and software design of the ASCCbot makes it a… (more)

Subjects/Keywords: activity recognition; mobile robot; semantic mapping; telepresence

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

APA (6th Edition):

Li, G. (2011). ASCCbot: An Open Mobile Robot Platform. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/10237

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):

Li, Gang. “ASCCbot: An Open Mobile Robot Platform.” 2011. Thesis, Oklahoma State University. Accessed April 20, 2019. http://hdl.handle.net/11244/10237.

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

MLA Handbook (7th Edition):

Li, Gang. “ASCCbot: An Open Mobile Robot Platform.” 2011. Web. 20 Apr 2019.

Vancouver:

Li G. ASCCbot: An Open Mobile Robot Platform. [Internet] [Thesis]. Oklahoma State University; 2011. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/11244/10237.

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

Council of Science Editors:

Li G. ASCCbot: An Open Mobile Robot Platform. [Thesis]. Oklahoma State University; 2011. Available from: http://hdl.handle.net/11244/10237

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


Robert Gordon University

15. Bashir, Sulaimon A. Change detection for activity recognition.

Degree: PhD, 2017, Robert Gordon University

Activity Recognition is concerned with identifying the physical state of a user at a particular point in time. Activity recognition task requires the training of… (more)

Subjects/Keywords: Activity recognition; Change detection; Classification algorithm; Sensors

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APA (6th Edition):

Bashir, S. A. (2017). Change detection for activity recognition. (Doctoral Dissertation). Robert Gordon University. Retrieved from http://hdl.handle.net/10059/3104

Chicago Manual of Style (16th Edition):

Bashir, Sulaimon A. “Change detection for activity recognition.” 2017. Doctoral Dissertation, Robert Gordon University. Accessed April 20, 2019. http://hdl.handle.net/10059/3104.

MLA Handbook (7th Edition):

Bashir, Sulaimon A. “Change detection for activity recognition.” 2017. Web. 20 Apr 2019.

Vancouver:

Bashir SA. Change detection for activity recognition. [Internet] [Doctoral dissertation]. Robert Gordon University; 2017. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/10059/3104.

Council of Science Editors:

Bashir SA. Change detection for activity recognition. [Doctoral Dissertation]. Robert Gordon University; 2017. Available from: http://hdl.handle.net/10059/3104


University of Houston

16. Sharma, Sarthak 1994-. Device Free Activity Recognition using Ultra-Wideband Radio Communication.

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

 Human Activity Recognition (HAR) is a fundamental building block in many Internet of Things (IoT) applications. Although there has been a lot of interest in… (more)

Subjects/Keywords: Ultra-Wideband; Device Free; activity recognition

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

APA (6th Edition):

Sharma, S. 1. (2018). Device Free Activity Recognition using Ultra-Wideband Radio Communication. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3303

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):

Sharma, Sarthak 1994-. “Device Free Activity Recognition using Ultra-Wideband Radio Communication.” 2018. Thesis, University of Houston. Accessed April 20, 2019. http://hdl.handle.net/10657/3303.

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

MLA Handbook (7th Edition):

Sharma, Sarthak 1994-. “Device Free Activity Recognition using Ultra-Wideband Radio Communication.” 2018. Web. 20 Apr 2019.

Vancouver:

Sharma S1. Device Free Activity Recognition using Ultra-Wideband Radio Communication. [Internet] [Thesis]. University of Houston; 2018. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/10657/3303.

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

Council of Science Editors:

Sharma S1. Device Free Activity Recognition using Ultra-Wideband Radio Communication. [Thesis]. University of Houston; 2018. Available from: http://hdl.handle.net/10657/3303

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. Wei, Bo. Embedded Sensing for Acoustic Classification, Activity Recognition and Localisation.

Degree: Computer Science & Engineering, 2015, University of New South Wales

 Embedded sensing aims to use low-cost computing, sensing and communication components to realise various sensing tasks. Embedded sensing has been successfully used in different applications.… (more)

Subjects/Keywords: Activity recognition; Embedded sensing; Acoustic classification; Localisation

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APA (6th Edition):

Wei, B. (2015). Embedded Sensing for Acoustic Classification, Activity Recognition and Localisation. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/54910 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36161/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Wei, Bo. “Embedded Sensing for Acoustic Classification, Activity Recognition and Localisation.” 2015. Doctoral Dissertation, University of New South Wales. Accessed April 20, 2019. http://handle.unsw.edu.au/1959.4/54910 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36161/SOURCE02?view=true.

MLA Handbook (7th Edition):

Wei, Bo. “Embedded Sensing for Acoustic Classification, Activity Recognition and Localisation.” 2015. Web. 20 Apr 2019.

Vancouver:

Wei B. Embedded Sensing for Acoustic Classification, Activity Recognition and Localisation. [Internet] [Doctoral dissertation]. University of New South Wales; 2015. [cited 2019 Apr 20]. Available from: http://handle.unsw.edu.au/1959.4/54910 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36161/SOURCE02?view=true.

Council of Science Editors:

Wei B. Embedded Sensing for Acoustic Classification, Activity Recognition and Localisation. [Doctoral Dissertation]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/54910 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36161/SOURCE02?view=true

18. Zhu, Shangyue. Human activity localization and recognation based on radar sensors for smart homes.

Degree: Thesis (M.S.), 2017, Ball State University

 The smart home is going through a rapid development in which predicting behaviors provides convenient service in human daily life. Tracking a user and recognizing… (more)

Subjects/Keywords: Acoustic localization.; Human activity recognition.; Home automation.

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

APA (6th Edition):

Zhu, S. (2017). Human activity localization and recognation based on radar sensors for smart homes. (Masters Thesis). Ball State University. Retrieved from http://cardinalscholar.bsu.edu/handle/123456789/201073

Chicago Manual of Style (16th Edition):

Zhu, Shangyue. “Human activity localization and recognation based on radar sensors for smart homes.” 2017. Masters Thesis, Ball State University. Accessed April 20, 2019. http://cardinalscholar.bsu.edu/handle/123456789/201073.

MLA Handbook (7th Edition):

Zhu, Shangyue. “Human activity localization and recognation based on radar sensors for smart homes.” 2017. Web. 20 Apr 2019.

Vancouver:

Zhu S. Human activity localization and recognation based on radar sensors for smart homes. [Internet] [Masters thesis]. Ball State University; 2017. [cited 2019 Apr 20]. Available from: http://cardinalscholar.bsu.edu/handle/123456789/201073.

Council of Science Editors:

Zhu S. Human activity localization and recognation based on radar sensors for smart homes. [Masters Thesis]. Ball State University; 2017. Available from: http://cardinalscholar.bsu.edu/handle/123456789/201073


University of Georgia

19. Aitha, Naveen Kumar. A hybrid multi-layer wavelet-based video encoding scheme for computer vision applications on mobile resource constrained devices.

Degree: MS, Computer Science, 2010, University of Georgia

 The use of multimedia-enabled mobile devices such as pocket PC's, smart cell phones and PDA's is increasing by the day and at a rapid pace.… (more)

Subjects/Keywords: layered media; Video streaming; Activity Recognition; Face Recognition

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

APA (6th Edition):

Aitha, N. K. (2010). A hybrid multi-layer wavelet-based video encoding scheme for computer vision applications on mobile resource constrained devices. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/aitha_naveen-kumar_201012_ms

Chicago Manual of Style (16th Edition):

Aitha, Naveen Kumar. “A hybrid multi-layer wavelet-based video encoding scheme for computer vision applications on mobile resource constrained devices.” 2010. Masters Thesis, University of Georgia. Accessed April 20, 2019. http://purl.galileo.usg.edu/uga_etd/aitha_naveen-kumar_201012_ms.

MLA Handbook (7th Edition):

Aitha, Naveen Kumar. “A hybrid multi-layer wavelet-based video encoding scheme for computer vision applications on mobile resource constrained devices.” 2010. Web. 20 Apr 2019.

Vancouver:

Aitha NK. A hybrid multi-layer wavelet-based video encoding scheme for computer vision applications on mobile resource constrained devices. [Internet] [Masters thesis]. University of Georgia; 2010. [cited 2019 Apr 20]. Available from: http://purl.galileo.usg.edu/uga_etd/aitha_naveen-kumar_201012_ms.

Council of Science Editors:

Aitha NK. A hybrid multi-layer wavelet-based video encoding scheme for computer vision applications on mobile resource constrained devices. [Masters Thesis]. University of Georgia; 2010. Available from: http://purl.galileo.usg.edu/uga_etd/aitha_naveen-kumar_201012_ms


University of Illinois – Urbana-Champaign

20. Yu, Wenbo. Good-walk recognition using Android smartphone accelerometer with application on senior patients.

Degree: MS, Computer Science, 2016, University of Illinois – Urbana-Champaign

 Good walk from one's everyday activities can be used towards chronic disease diagnosis. Smartphones have become increasingly popular among people across ages. Properties including light… (more)

Subjects/Keywords: bioinformatics; walk recognition; activity recognition; smartphone; accelerometer; senior patient

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

APA (6th Edition):

Yu, W. (2016). Good-walk recognition using Android smartphone accelerometer with application on senior patients. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/90611

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

Chicago Manual of Style (16th Edition):

Yu, Wenbo. “Good-walk recognition using Android smartphone accelerometer with application on senior patients.” 2016. Thesis, University of Illinois – Urbana-Champaign. Accessed April 20, 2019. http://hdl.handle.net/2142/90611.

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

MLA Handbook (7th Edition):

Yu, Wenbo. “Good-walk recognition using Android smartphone accelerometer with application on senior patients.” 2016. Web. 20 Apr 2019.

Vancouver:

Yu W. Good-walk recognition using Android smartphone accelerometer with application on senior patients. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/2142/90611.

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

Council of Science Editors:

Yu W. Good-walk recognition using Android smartphone accelerometer with application on senior patients. [Thesis]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/90611

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


University of Adelaide

21. Ruan, Wenjie. Device-free human localization and activity recognition for supporting the independent living of the elderly.

Degree: 2017, University of Adelaide

 Given the continuous growth of the aging population, the cost of health care, and the preference that the elderly want to live independently and safely… (more)

Subjects/Keywords: indoor localization; human activity recognition; RFID; hand gesture recognition; tensor; decomposition

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APA (6th Edition):

Ruan, W. (2017). Device-free human localization and activity recognition for supporting the independent living of the elderly. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/112860

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):

Ruan, Wenjie. “Device-free human localization and activity recognition for supporting the independent living of the elderly.” 2017. Thesis, University of Adelaide. Accessed April 20, 2019. http://hdl.handle.net/2440/112860.

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

MLA Handbook (7th Edition):

Ruan, Wenjie. “Device-free human localization and activity recognition for supporting the independent living of the elderly.” 2017. Web. 20 Apr 2019.

Vancouver:

Ruan W. Device-free human localization and activity recognition for supporting the independent living of the elderly. [Internet] [Thesis]. University of Adelaide; 2017. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/2440/112860.

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

Council of Science Editors:

Ruan W. Device-free human localization and activity recognition for supporting the independent living of the elderly. [Thesis]. University of Adelaide; 2017. Available from: http://hdl.handle.net/2440/112860

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


Hong Kong University of Science and Technology

22. Sun, Lin ECE. Deeply learned representations for human action recognition.

Degree: 2018, Hong Kong University of Science and Technology

 Unlike in image recognition, human actions in video sequences are three-dimensional (3D) spatio-temporal signals characterizing both the visual appearance and motion dynamics of the involved… (more)

Subjects/Keywords: Human activity recognition; Data processing; Pattern recognition systems; Computer vision

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APA (6th Edition):

Sun, L. E. (2018). Deeply learned representations for human action recognition. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-991012637468003412 ; http://repository.ust.hk/ir/bitstream/1783.1-96003/1/th_redirect.html

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):

Sun, Lin ECE. “Deeply learned representations for human action recognition.” 2018. Thesis, Hong Kong University of Science and Technology. Accessed April 20, 2019. https://doi.org/10.14711/thesis-991012637468003412 ; http://repository.ust.hk/ir/bitstream/1783.1-96003/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Sun, Lin ECE. “Deeply learned representations for human action recognition.” 2018. Web. 20 Apr 2019.

Vancouver:

Sun LE. Deeply learned representations for human action recognition. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2018. [cited 2019 Apr 20]. Available from: https://doi.org/10.14711/thesis-991012637468003412 ; http://repository.ust.hk/ir/bitstream/1783.1-96003/1/th_redirect.html.

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

Council of Science Editors:

Sun LE. Deeply learned representations for human action recognition. [Thesis]. Hong Kong University of Science and Technology; 2018. Available from: https://doi.org/10.14711/thesis-991012637468003412 ; http://repository.ust.hk/ir/bitstream/1783.1-96003/1/th_redirect.html

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


University of Southern California

23. Banerjee, Prithviraj. Incorporating aggregate feature statistics in structured dynamical models for human activity recognition.

Degree: PhD, Computer Science, 2014, University of Southern California

 Human action recognition in videos is a central problem of computer vision, with numerous applications in the fields of video surveillance, data mining and human… (more)

Subjects/Keywords: computer vision; machine learning; human activity recognition; activity detection; graphical models

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APA (6th Edition):

Banerjee, P. (2014). Incorporating aggregate feature statistics in structured dynamical models for human activity recognition. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438

Chicago Manual of Style (16th Edition):

Banerjee, Prithviraj. “Incorporating aggregate feature statistics in structured dynamical models for human activity recognition.” 2014. Doctoral Dissertation, University of Southern California. Accessed April 20, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438.

MLA Handbook (7th Edition):

Banerjee, Prithviraj. “Incorporating aggregate feature statistics in structured dynamical models for human activity recognition.” 2014. Web. 20 Apr 2019.

Vancouver:

Banerjee P. Incorporating aggregate feature statistics in structured dynamical models for human activity recognition. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Apr 20]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438.

Council of Science Editors:

Banerjee P. Incorporating aggregate feature statistics in structured dynamical models for human activity recognition. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438


Colorado School of Mines

24. Reily, Brian J. Human activity recognition and gymnastics analysis through depth imagery.

Degree: MS(M.S.), Electrical Engineering and Computer Science, 2016, Colorado School of Mines

 Depth imagery is transforming many areas of computer vision, such as object recognition, human detection, human activity recognition, and sports analysis. The goal of my… (more)

Subjects/Keywords: Activity prediction; Activity recognition; Depth imagery; Gymnastics; Image segmentation

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APA (6th Edition):

Reily, B. J. (2016). Human activity recognition and gymnastics analysis through depth imagery. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/170153

Chicago Manual of Style (16th Edition):

Reily, Brian J. “Human activity recognition and gymnastics analysis through depth imagery.” 2016. Masters Thesis, Colorado School of Mines. Accessed April 20, 2019. http://hdl.handle.net/11124/170153.

MLA Handbook (7th Edition):

Reily, Brian J. “Human activity recognition and gymnastics analysis through depth imagery.” 2016. Web. 20 Apr 2019.

Vancouver:

Reily BJ. Human activity recognition and gymnastics analysis through depth imagery. [Internet] [Masters thesis]. Colorado School of Mines; 2016. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/11124/170153.

Council of Science Editors:

Reily BJ. Human activity recognition and gymnastics analysis through depth imagery. [Masters Thesis]. Colorado School of Mines; 2016. Available from: http://hdl.handle.net/11124/170153


Washington State University

25. [No author]. Scaling Activity Discovery and Recognition to Large, Complex Datasets .

Degree: 2011, Washington State University

 In the past decade, activity discovery and recognition has been studied by many researchers. However there are still many challenges to be addressed before deploying… (more)

Subjects/Keywords: Computer Science; Activity Discovery; Activity Recognition; Data Mining; Machine Learning

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APA (6th Edition):

author], [. (2011). Scaling Activity Discovery and Recognition to Large, Complex Datasets . (Thesis). Washington State University. Retrieved from http://hdl.handle.net/2376/2861

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):

author], [No. “Scaling Activity Discovery and Recognition to Large, Complex Datasets .” 2011. Thesis, Washington State University. Accessed April 20, 2019. http://hdl.handle.net/2376/2861.

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

MLA Handbook (7th Edition):

author], [No. “Scaling Activity Discovery and Recognition to Large, Complex Datasets .” 2011. Web. 20 Apr 2019.

Vancouver:

author] [. Scaling Activity Discovery and Recognition to Large, Complex Datasets . [Internet] [Thesis]. Washington State University; 2011. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/2376/2861.

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

Council of Science Editors:

author] [. Scaling Activity Discovery and Recognition to Large, Complex Datasets . [Thesis]. Washington State University; 2011. Available from: http://hdl.handle.net/2376/2861

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

26. Gani, Md Osman. A Novel Approach to Complex Human Activity Recognition.

Degree: 2017, Marquette University

 Human activity recognition is a technology that offers automatic recognition of what a person is doing with respect to body motion and function. The main… (more)

Subjects/Keywords: Complex Human Activity; Human Activity Recognition; Localization; Simple Human Activity; Computer Sciences; Hardware Systems

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APA (6th Edition):

Gani, M. O. (2017). A Novel Approach to Complex Human Activity Recognition. (Thesis). Marquette University. Retrieved from https://epublications.marquette.edu/dissertations_mu/701

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):

Gani, Md Osman. “A Novel Approach to Complex Human Activity Recognition.” 2017. Thesis, Marquette University. Accessed April 20, 2019. https://epublications.marquette.edu/dissertations_mu/701.

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

MLA Handbook (7th Edition):

Gani, Md Osman. “A Novel Approach to Complex Human Activity Recognition.” 2017. Web. 20 Apr 2019.

Vancouver:

Gani MO. A Novel Approach to Complex Human Activity Recognition. [Internet] [Thesis]. Marquette University; 2017. [cited 2019 Apr 20]. Available from: https://epublications.marquette.edu/dissertations_mu/701.

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

Council of Science Editors:

Gani MO. A Novel Approach to Complex Human Activity Recognition. [Thesis]. Marquette University; 2017. Available from: https://epublications.marquette.edu/dissertations_mu/701

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


University of Oulu

27. Siirtola, P. (Pekka). Recognizing human activities based on wearable inertial measurements:methods and applications.

Degree: 2015, University of Oulu

Abstract Inertial sensors are devices that measure movement, and therefore, when they are attached to a body, they can be used to measure human movements.… (more)

Subjects/Keywords: activity recognition; inertial sensors; pattern recognition; hahmontunnistus; liikettä mittaavat anturit; toimien tunnistaminen

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

APA (6th Edition):

Siirtola, P. (. (2015). Recognizing human activities based on wearable inertial measurements:methods and applications. (Doctoral Dissertation). University of Oulu. Retrieved from http://urn.fi/urn:isbn:9789526207698

Chicago Manual of Style (16th Edition):

Siirtola, P (Pekka). “Recognizing human activities based on wearable inertial measurements:methods and applications.” 2015. Doctoral Dissertation, University of Oulu. Accessed April 20, 2019. http://urn.fi/urn:isbn:9789526207698.

MLA Handbook (7th Edition):

Siirtola, P (Pekka). “Recognizing human activities based on wearable inertial measurements:methods and applications.” 2015. Web. 20 Apr 2019.

Vancouver:

Siirtola P(. Recognizing human activities based on wearable inertial measurements:methods and applications. [Internet] [Doctoral dissertation]. University of Oulu; 2015. [cited 2019 Apr 20]. Available from: http://urn.fi/urn:isbn:9789526207698.

Council of Science Editors:

Siirtola P(. Recognizing human activities based on wearable inertial measurements:methods and applications. [Doctoral Dissertation]. University of Oulu; 2015. Available from: http://urn.fi/urn:isbn:9789526207698


University of KwaZulu-Natal

28. [No author]. Handwritten signature verification using locally optimized distance-based classification.

Degree: Computer science, 2013, University of KwaZulu-Natal

 Although handwritten signature verification has been extensively researched, it has not achieved optimum accuracy rate. Therefore, efficient and accurate signature verification techniques are required since… (more)

Subjects/Keywords: Biometric identification.; Pattern recognition systems.; Human activity recognition.; Signatures (Writing); Markov processes.; Computer science.

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APA (6th Edition):

author], [. (2013). Handwritten signature verification using locally optimized distance-based classification. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/10112

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):

author], [No. “Handwritten signature verification using locally optimized distance-based classification. ” 2013. Thesis, University of KwaZulu-Natal. Accessed April 20, 2019. http://hdl.handle.net/10413/10112.

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

MLA Handbook (7th Edition):

author], [No. “Handwritten signature verification using locally optimized distance-based classification. ” 2013. Web. 20 Apr 2019.

Vancouver:

author] [. Handwritten signature verification using locally optimized distance-based classification. [Internet] [Thesis]. University of KwaZulu-Natal; 2013. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/10413/10112.

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

Council of Science Editors:

author] [. Handwritten signature verification using locally optimized distance-based classification. [Thesis]. University of KwaZulu-Natal; 2013. Available from: http://hdl.handle.net/10413/10112

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


Queens University

29. Elhoushi, Mostafa. Advanced Motion Mode Recognition for Portable Navigation .

Degree: Electrical and Computer Engineering, 2015, Queens University

 Portable navigation is increasingly becoming an essential part of our lives. Knowing a person’s position and velocity using a portable device, such as a smartphone,… (more)

Subjects/Keywords: Pattern Recognition; Sensor Fusion; Inertial Navigation; Activity Recognition; Portable Navigation; Machine Learning

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APA (6th Edition):

Elhoushi, M. (2015). Advanced Motion Mode Recognition for Portable Navigation . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/12790

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):

Elhoushi, Mostafa. “Advanced Motion Mode Recognition for Portable Navigation .” 2015. Thesis, Queens University. Accessed April 20, 2019. http://hdl.handle.net/1974/12790.

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

MLA Handbook (7th Edition):

Elhoushi, Mostafa. “Advanced Motion Mode Recognition for Portable Navigation .” 2015. Web. 20 Apr 2019.

Vancouver:

Elhoushi M. Advanced Motion Mode Recognition for Portable Navigation . [Internet] [Thesis]. Queens University; 2015. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/1974/12790.

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

Council of Science Editors:

Elhoushi M. Advanced Motion Mode Recognition for Portable Navigation . [Thesis]. Queens University; 2015. Available from: http://hdl.handle.net/1974/12790

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


University of Texas – Austin

30. Gupta, Sonal. Activity retrieval in closed captioned videos.

Degree: Computer Sciences, 2009, University of Texas – Austin

 Recognizing activities in real-world videos is a difficult problem exacerbated by background clutter, changes in camera angle & zoom, occlusion and rapid camera movements. Large… (more)

Subjects/Keywords: Activity Recognition; Action Recognition; Video Retrieval; Machine Learning; Computer Vision; Multimedia; Closed Captions

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APA (6th Edition):

Gupta, S. (2009). Activity retrieval in closed captioned videos. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-08-305

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):

Gupta, Sonal. “Activity retrieval in closed captioned videos.” 2009. Thesis, University of Texas – Austin. Accessed April 20, 2019. http://hdl.handle.net/2152/ETD-UT-2009-08-305.

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

MLA Handbook (7th Edition):

Gupta, Sonal. “Activity retrieval in closed captioned videos.” 2009. Web. 20 Apr 2019.

Vancouver:

Gupta S. Activity retrieval in closed captioned videos. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Apr 20]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-305.

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

Council of Science Editors:

Gupta S. Activity retrieval in closed captioned videos. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-08-305

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

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