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You searched for +publisher:"Penn State University" +contributor:("Yanxi Liu, Thesis Advisor/Co-Advisor"). Showing records 1 – 5 of 5 total matches.

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Penn State University

1. Wang, Tianhe. 3D Human pose estimation on Taiji sequence.

Degree: 2018, Penn State University

 Human pose estimation is a task that has been extensively studied in the field of computer vision. Given a video frame or an image, a… (more)

Subjects/Keywords: Pose estimation; Neural Networks; Motion Capture; Regression

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

APA (6th Edition):

Wang, T. (2018). 3D Human pose estimation on Taiji sequence. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15682tzw43

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):

Wang, Tianhe. “3D Human pose estimation on Taiji sequence.” 2018. Thesis, Penn State University. Accessed November 30, 2020. https://submit-etda.libraries.psu.edu/catalog/15682tzw43.

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

MLA Handbook (7th Edition):

Wang, Tianhe. “3D Human pose estimation on Taiji sequence.” 2018. Web. 30 Nov 2020.

Vancouver:

Wang T. 3D Human pose estimation on Taiji sequence. [Internet] [Thesis]. Penn State University; 2018. [cited 2020 Nov 30]. Available from: https://submit-etda.libraries.psu.edu/catalog/15682tzw43.

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

Council of Science Editors:

Wang T. 3D Human pose estimation on Taiji sequence. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/15682tzw43

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


Penn State University

2. Fry, Jonathan Richard. An Investigation of Wavelet Features for Automated Biomedical Image Classification .

Degree: 2012, Penn State University

 In this thesis, we present a systematic investigation of the wavelet feature space for automated biological and biomedical image classification. This thesis addresses the lack… (more)

Subjects/Keywords: wavelet; feature space; classification; machine learning; pattern recognition; image analysis; feature selection

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

APA (6th Edition):

Fry, J. R. (2012). An Investigation of Wavelet Features for Automated Biomedical Image Classification . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16362

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):

Fry, Jonathan Richard. “An Investigation of Wavelet Features for Automated Biomedical Image Classification .” 2012. Thesis, Penn State University. Accessed November 30, 2020. https://submit-etda.libraries.psu.edu/catalog/16362.

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

MLA Handbook (7th Edition):

Fry, Jonathan Richard. “An Investigation of Wavelet Features for Automated Biomedical Image Classification .” 2012. Web. 30 Nov 2020.

Vancouver:

Fry JR. An Investigation of Wavelet Features for Automated Biomedical Image Classification . [Internet] [Thesis]. Penn State University; 2012. [cited 2020 Nov 30]. Available from: https://submit-etda.libraries.psu.edu/catalog/16362.

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

Council of Science Editors:

Fry JR. An Investigation of Wavelet Features for Automated Biomedical Image Classification . [Thesis]. Penn State University; 2012. Available from: https://submit-etda.libraries.psu.edu/catalog/16362

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


Penn State University

3. Raja, Anand. TOWARDS UNDERSTANDING PEOPLE IN VIDEOS .

Degree: 2011, Penn State University

 The last few years have seen an explosion of online video content. A vast majority of these videos contain people, and understanding where people are… (more)

Subjects/Keywords: visual storyboard; action recognition; tracking; people detection; computer vision; character matching

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

APA (6th Edition):

Raja, A. (2011). TOWARDS UNDERSTANDING PEOPLE IN VIDEOS . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/11510

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):

Raja, Anand. “TOWARDS UNDERSTANDING PEOPLE IN VIDEOS .” 2011. Thesis, Penn State University. Accessed November 30, 2020. https://submit-etda.libraries.psu.edu/catalog/11510.

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

MLA Handbook (7th Edition):

Raja, Anand. “TOWARDS UNDERSTANDING PEOPLE IN VIDEOS .” 2011. Web. 30 Nov 2020.

Vancouver:

Raja A. TOWARDS UNDERSTANDING PEOPLE IN VIDEOS . [Internet] [Thesis]. Penn State University; 2011. [cited 2020 Nov 30]. Available from: https://submit-etda.libraries.psu.edu/catalog/11510.

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

Council of Science Editors:

Raja A. TOWARDS UNDERSTANDING PEOPLE IN VIDEOS . [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/11510

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


Penn State University

4. Yu, Chen-Ping. Statistical Asymmetry-based Automatic Brain Tumor Detection from 3D MR Images .

Degree: 2010, Penn State University

 The detection and accurate segmentation of brain tumors from MR images is an important and necessary step for early diagnosis, optimized treatment, surgical planning, and… (more)

Subjects/Keywords: tumor volume segmentation; 3D blob detection; brain tumor detection; brain asymmetry

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

APA (6th Edition):

Yu, C. (2010). Statistical Asymmetry-based Automatic Brain Tumor Detection from 3D MR Images . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/10847

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, Chen-Ping. “Statistical Asymmetry-based Automatic Brain Tumor Detection from 3D MR Images .” 2010. Thesis, Penn State University. Accessed November 30, 2020. https://submit-etda.libraries.psu.edu/catalog/10847.

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

MLA Handbook (7th Edition):

Yu, Chen-Ping. “Statistical Asymmetry-based Automatic Brain Tumor Detection from 3D MR Images .” 2010. Web. 30 Nov 2020.

Vancouver:

Yu C. Statistical Asymmetry-based Automatic Brain Tumor Detection from 3D MR Images . [Internet] [Thesis]. Penn State University; 2010. [cited 2020 Nov 30]. Available from: https://submit-etda.libraries.psu.edu/catalog/10847.

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

Council of Science Editors:

Yu C. Statistical Asymmetry-based Automatic Brain Tumor Detection from 3D MR Images . [Thesis]. Penn State University; 2010. Available from: https://submit-etda.libraries.psu.edu/catalog/10847

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


Penn State University

5. Kashyap, Somesh. A COMPUTATIONAL FRAMEWORK FOR DISCRIMINATIVE ANALYSIS OF HIGH DIMENSIONAL BIOMEDICAL IMAGE DATA .

Degree: 2010, Penn State University

 In this work we propose, implement and evaluate a discriminative computational pipeline to address the problem of feature generation, feature screening and feature subset selection… (more)

Subjects/Keywords: Expression; Machine learning; Plant; 3D Face; Age; Brain; Asymmetry; Gender; Computer-Aided Diagnosis; Alzheimer; Pipeline

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

APA (6th Edition):

Kashyap, S. (2010). A COMPUTATIONAL FRAMEWORK FOR DISCRIMINATIVE ANALYSIS OF HIGH DIMENSIONAL BIOMEDICAL IMAGE DATA . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/9627

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):

Kashyap, Somesh. “A COMPUTATIONAL FRAMEWORK FOR DISCRIMINATIVE ANALYSIS OF HIGH DIMENSIONAL BIOMEDICAL IMAGE DATA .” 2010. Thesis, Penn State University. Accessed November 30, 2020. https://submit-etda.libraries.psu.edu/catalog/9627.

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

MLA Handbook (7th Edition):

Kashyap, Somesh. “A COMPUTATIONAL FRAMEWORK FOR DISCRIMINATIVE ANALYSIS OF HIGH DIMENSIONAL BIOMEDICAL IMAGE DATA .” 2010. Web. 30 Nov 2020.

Vancouver:

Kashyap S. A COMPUTATIONAL FRAMEWORK FOR DISCRIMINATIVE ANALYSIS OF HIGH DIMENSIONAL BIOMEDICAL IMAGE DATA . [Internet] [Thesis]. Penn State University; 2010. [cited 2020 Nov 30]. Available from: https://submit-etda.libraries.psu.edu/catalog/9627.

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

Council of Science Editors:

Kashyap S. A COMPUTATIONAL FRAMEWORK FOR DISCRIMINATIVE ANALYSIS OF HIGH DIMENSIONAL BIOMEDICAL IMAGE DATA . [Thesis]. Penn State University; 2010. Available from: https://submit-etda.libraries.psu.edu/catalog/9627

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

.