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You searched for subject:(CNNs). Showing records 1 – 15 of 15 total matches.

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Georgia Tech

1. Dedhia, Vaibhav. Scene flow for autonomous navigation.

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

 Today, there are various different paradigms for vision based autonomous navigation: mediated perception approaches that parse an entire scene to make driving decision, a direct… (more)

Subjects/Keywords: Autonomous navigation; CNNs; Computer vision

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APA (6th Edition):

Dedhia, V. (2018). Scene flow for autonomous navigation. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59948

Chicago Manual of Style (16th Edition):

Dedhia, Vaibhav. “Scene flow for autonomous navigation.” 2018. Masters Thesis, Georgia Tech. Accessed January 17, 2019. http://hdl.handle.net/1853/59948.

MLA Handbook (7th Edition):

Dedhia, Vaibhav. “Scene flow for autonomous navigation.” 2018. Web. 17 Jan 2019.

Vancouver:

Dedhia V. Scene flow for autonomous navigation. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2019 Jan 17]. Available from: http://hdl.handle.net/1853/59948.

Council of Science Editors:

Dedhia V. Scene flow for autonomous navigation. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59948


Rochester Institute of Technology

2. Oruganti, Ram Manohar. Image Description using Deep Neural Networks.

Degree: MS, Computer Engineering, 2016, Rochester Institute of Technology

  Current research in computer vision and machine learning has demonstrated some great abilities at detecting and recognizing objects in natural images. Current state-of-the-art results… (more)

Subjects/Keywords: CNNs; Deep learning; Image description; LSTMs; Multi-modal applications; Scene analysis

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APA (6th Edition):

Oruganti, R. M. (2016). Image Description using Deep Neural Networks. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9043

Chicago Manual of Style (16th Edition):

Oruganti, Ram Manohar. “Image Description using Deep Neural Networks.” 2016. Masters Thesis, Rochester Institute of Technology. Accessed January 17, 2019. https://scholarworks.rit.edu/theses/9043.

MLA Handbook (7th Edition):

Oruganti, Ram Manohar. “Image Description using Deep Neural Networks.” 2016. Web. 17 Jan 2019.

Vancouver:

Oruganti RM. Image Description using Deep Neural Networks. [Internet] [Masters thesis]. Rochester Institute of Technology; 2016. [cited 2019 Jan 17]. Available from: https://scholarworks.rit.edu/theses/9043.

Council of Science Editors:

Oruganti RM. Image Description using Deep Neural Networks. [Masters Thesis]. Rochester Institute of Technology; 2016. Available from: https://scholarworks.rit.edu/theses/9043


Lehigh University

3. He, Yuanhao. Drosophila Heart Recognition System using Convolutional Neural Networks.

Degree: MS, Electrical and Computer Engineering, 2015, Lehigh University

 In this thesis, we introduced a new method of marking the heart region of Drosophila in its different living stages which are known as larva,… (more)

Subjects/Keywords: CNNs; Convolutional Neural Networks; Drosophila Heart; OCM; optical coherence microscopy; Electrical and Computer Engineering

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APA (6th Edition):

He, Y. (2015). Drosophila Heart Recognition System using Convolutional Neural Networks. (Thesis). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/4287

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):

He, Yuanhao. “Drosophila Heart Recognition System using Convolutional Neural Networks.” 2015. Thesis, Lehigh University. Accessed January 17, 2019. https://preserve.lehigh.edu/etd/4287.

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

MLA Handbook (7th Edition):

He, Yuanhao. “Drosophila Heart Recognition System using Convolutional Neural Networks.” 2015. Web. 17 Jan 2019.

Vancouver:

He Y. Drosophila Heart Recognition System using Convolutional Neural Networks. [Internet] [Thesis]. Lehigh University; 2015. [cited 2019 Jan 17]. Available from: https://preserve.lehigh.edu/etd/4287.

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

Council of Science Editors:

He Y. Drosophila Heart Recognition System using Convolutional Neural Networks. [Thesis]. Lehigh University; 2015. Available from: https://preserve.lehigh.edu/etd/4287

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


Cal Poly

4. Venkatesh, Anirudh. Object Tracking in Games using Convolutional Neural Networks.

Degree: MS, Computer Science, 2018, Cal Poly

  Computer vision research has been growing rapidly over the last decade. Recent advancements in the field have been widely used in staple products across… (more)

Subjects/Keywords: Convolutional Neural Networks; YOLO; Games; CNNs; Neural Networks; Object Detection; Computer Engineering

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APA (6th Edition):

Venkatesh, A. (2018). Object Tracking in Games using Convolutional Neural Networks. (Masters Thesis). Cal Poly. Retrieved from https://digitalcommons.calpoly.edu/theses/1845

Chicago Manual of Style (16th Edition):

Venkatesh, Anirudh. “Object Tracking in Games using Convolutional Neural Networks.” 2018. Masters Thesis, Cal Poly. Accessed January 17, 2019. https://digitalcommons.calpoly.edu/theses/1845.

MLA Handbook (7th Edition):

Venkatesh, Anirudh. “Object Tracking in Games using Convolutional Neural Networks.” 2018. Web. 17 Jan 2019.

Vancouver:

Venkatesh A. Object Tracking in Games using Convolutional Neural Networks. [Internet] [Masters thesis]. Cal Poly; 2018. [cited 2019 Jan 17]. Available from: https://digitalcommons.calpoly.edu/theses/1845.

Council of Science Editors:

Venkatesh A. Object Tracking in Games using Convolutional Neural Networks. [Masters Thesis]. Cal Poly; 2018. Available from: https://digitalcommons.calpoly.edu/theses/1845


Rochester Institute of Technology

5. Dhamdhere, Rohan N. Meta Learning for Graph Neural Networks.

Degree: MS, Computer Engineering, 2018, Rochester Institute of Technology

  Deep learning has enabled incredible advances in pattern recognition such as the fields of computer vision and natural language processing. One of the most… (more)

Subjects/Keywords: Convolutional neural networks; Deep learning; Evolutionary algorithms; Graph CNNs; Meta learning; Protein graph datasets

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APA (6th Edition):

Dhamdhere, R. N. (2018). Meta Learning for Graph Neural Networks. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9917

Chicago Manual of Style (16th Edition):

Dhamdhere, Rohan N. “Meta Learning for Graph Neural Networks.” 2018. Masters Thesis, Rochester Institute of Technology. Accessed January 17, 2019. https://scholarworks.rit.edu/theses/9917.

MLA Handbook (7th Edition):

Dhamdhere, Rohan N. “Meta Learning for Graph Neural Networks.” 2018. Web. 17 Jan 2019.

Vancouver:

Dhamdhere RN. Meta Learning for Graph Neural Networks. [Internet] [Masters thesis]. Rochester Institute of Technology; 2018. [cited 2019 Jan 17]. Available from: https://scholarworks.rit.edu/theses/9917.

Council of Science Editors:

Dhamdhere RN. Meta Learning for Graph Neural Networks. [Masters Thesis]. Rochester Institute of Technology; 2018. Available from: https://scholarworks.rit.edu/theses/9917


Universitat Ramon Llull

6. Viñoles Serra, Mireia. Dynamics of Two Neuron Cellular Neural Networks.

Degree: 2011, Universitat Ramon Llull

 In this dissertation we review the two neuron cellular neural network stability using the Lyapunov theory, and using the different local dynamic behavior derived from… (more)

Subjects/Keywords: classification problems; template design; limit cycles; problemas de clasificación; CNNs; diseño de plantillas; problems de classificació; disseny de plantilles; CNNs; ciclos límite; CNNs; cicles limit; Les TIC i la seva gestió; 537; 621.3

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

APA (6th Edition):

Viñoles Serra, M. (2011). Dynamics of Two Neuron Cellular Neural Networks. (Thesis). Universitat Ramon Llull. Retrieved from http://hdl.handle.net/10803/9154

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):

Viñoles Serra, Mireia. “Dynamics of Two Neuron Cellular Neural Networks.” 2011. Thesis, Universitat Ramon Llull. Accessed January 17, 2019. http://hdl.handle.net/10803/9154.

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

MLA Handbook (7th Edition):

Viñoles Serra, Mireia. “Dynamics of Two Neuron Cellular Neural Networks.” 2011. Web. 17 Jan 2019.

Vancouver:

Viñoles Serra M. Dynamics of Two Neuron Cellular Neural Networks. [Internet] [Thesis]. Universitat Ramon Llull; 2011. [cited 2019 Jan 17]. Available from: http://hdl.handle.net/10803/9154.

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

Council of Science Editors:

Viñoles Serra M. Dynamics of Two Neuron Cellular Neural Networks. [Thesis]. Universitat Ramon Llull; 2011. Available from: http://hdl.handle.net/10803/9154

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


Uppsala University

7. Tang, Hao. Bidirectional LSTM-CNNs-CRF Models for POS Tagging.

Degree: Linguistics and Philology, 2018, Uppsala University

  In order to achieve state-of-the-art performance for part-of-speech(POS) tagging, the traditional systems require a significant amount of hand-crafted features and data pre-processing. In this… (more)

Subjects/Keywords: bidirectional LSTM; part of speech; CNNs; CRF; byte pair encoding (BPE); Language Technology (Computational Linguistics); Språkteknologi (språkvetenskaplig databehandling)

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

APA (6th Edition):

Tang, H. (2018). Bidirectional LSTM-CNNs-CRF Models for POS Tagging. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-362823

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):

Tang, Hao. “Bidirectional LSTM-CNNs-CRF Models for POS Tagging.” 2018. Thesis, Uppsala University. Accessed January 17, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-362823.

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

MLA Handbook (7th Edition):

Tang, Hao. “Bidirectional LSTM-CNNs-CRF Models for POS Tagging.” 2018. Web. 17 Jan 2019.

Vancouver:

Tang H. Bidirectional LSTM-CNNs-CRF Models for POS Tagging. [Internet] [Thesis]. Uppsala University; 2018. [cited 2019 Jan 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-362823.

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

Council of Science Editors:

Tang H. Bidirectional LSTM-CNNs-CRF Models for POS Tagging. [Thesis]. Uppsala University; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-362823

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


AUT University

8. Wang, Hui. Real-time Face Detection and Recognition Based on Deep Learning .

Degree: AUT University

 Face recognition is one of the most important applications in video surveillance and computer vision. However, the conventional algorithms of face recognition are susceptible to… (more)

Subjects/Keywords: CNNs; Face recognition; Data augmentation; SSD; Inception v2

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APA (6th Edition):

Wang, H. (n.d.). Real-time Face Detection and Recognition Based on Deep Learning . (Thesis). AUT University. Retrieved from http://hdl.handle.net/10292/11866

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wang, Hui. “Real-time Face Detection and Recognition Based on Deep Learning .” Thesis, AUT University. Accessed January 17, 2019. http://hdl.handle.net/10292/11866.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wang, Hui. “Real-time Face Detection and Recognition Based on Deep Learning .” Web. 17 Jan 2019.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Wang H. Real-time Face Detection and Recognition Based on Deep Learning . [Internet] [Thesis]. AUT University; [cited 2019 Jan 17]. Available from: http://hdl.handle.net/10292/11866.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Wang H. Real-time Face Detection and Recognition Based on Deep Learning . [Thesis]. AUT University; Available from: http://hdl.handle.net/10292/11866

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.


Australian National University

9. Anwar, Saeed. Data-Driven Image Restoration .

Degree: 2018, Australian National University

 Every day many images are taken by digital cameras, and people are demanding visually accurate and pleasing result. Noise and blur degrade images captured by… (more)

Subjects/Keywords: Deblurring; Denoising; Class-Specific; Category-Specific; CNNs; Convolutional Neural Networks; Object Specific; Object deblurring; Object Denoising; Patch Similarity; Frequency bands

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APA (6th Edition):

Anwar, S. (2018). Data-Driven Image Restoration . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/148622

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):

Anwar, Saeed. “Data-Driven Image Restoration .” 2018. Thesis, Australian National University. Accessed January 17, 2019. http://hdl.handle.net/1885/148622.

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

MLA Handbook (7th Edition):

Anwar, Saeed. “Data-Driven Image Restoration .” 2018. Web. 17 Jan 2019.

Vancouver:

Anwar S. Data-Driven Image Restoration . [Internet] [Thesis]. Australian National University; 2018. [cited 2019 Jan 17]. Available from: http://hdl.handle.net/1885/148622.

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

Council of Science Editors:

Anwar S. Data-Driven Image Restoration . [Thesis]. Australian National University; 2018. Available from: http://hdl.handle.net/1885/148622

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


University of Cincinnati

10. MAILAVARAM, MADHURI. A STANDARD CELL LIBRARY USING CMOS TRANSCONDUCTANCE AMPLIFIERS FOR CELLULAR NEURAL NETWORKS.

Degree: MS, Engineering : Electrical Engineering, 2006, University of Cincinnati

 Cellular Neural Networks (CNNs) form a class of information-processing systems which like neural networks are large-scale nonlinear analog circuits performing real time parallel processing of… (more)

Subjects/Keywords: Cellular Neural Networks; CNNs; CMOS Transconductance Amplifier; Standard Cell Library of CNNS; Analog CMOS VLSI Implementation; CNN Image Processing Applications

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APA (6th Edition):

MAILAVARAM, M. (2006). A STANDARD CELL LIBRARY USING CMOS TRANSCONDUCTANCE AMPLIFIERS FOR CELLULAR NEURAL NETWORKS. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1140802889

Chicago Manual of Style (16th Edition):

MAILAVARAM, MADHURI. “A STANDARD CELL LIBRARY USING CMOS TRANSCONDUCTANCE AMPLIFIERS FOR CELLULAR NEURAL NETWORKS.” 2006. Masters Thesis, University of Cincinnati. Accessed January 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1140802889.

MLA Handbook (7th Edition):

MAILAVARAM, MADHURI. “A STANDARD CELL LIBRARY USING CMOS TRANSCONDUCTANCE AMPLIFIERS FOR CELLULAR NEURAL NETWORKS.” 2006. Web. 17 Jan 2019.

Vancouver:

MAILAVARAM M. A STANDARD CELL LIBRARY USING CMOS TRANSCONDUCTANCE AMPLIFIERS FOR CELLULAR NEURAL NETWORKS. [Internet] [Masters thesis]. University of Cincinnati; 2006. [cited 2019 Jan 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1140802889.

Council of Science Editors:

MAILAVARAM M. A STANDARD CELL LIBRARY USING CMOS TRANSCONDUCTANCE AMPLIFIERS FOR CELLULAR NEURAL NETWORKS. [Masters Thesis]. University of Cincinnati; 2006. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1140802889


KTH

11. Linder, Johannes. Modeling the intronic regulation of Alternative Splicing using Deep Convolutional Neural Nets.

Degree: Computer Science and Communication (CSC), 2015, KTH

This paper investigates the use of deep Convolutional Neural Networks for modeling the intronic regulation of Alternative Splicing on the basis of DNA sequence.… (more)

Subjects/Keywords: Machine Learning; Deep Learning; CNN; CNNs; Convolutional Neural Networks; Convolutional Neural Nets; Neural Networks; Neural Nets; Synthetic Biology; Alternative Splicing; AS; Splicing; DNA Regulation; Synthetic DNA; Massively Parallel Library; Maskinlärning; CNN; CNNs; Convolutional Neural Networks; Convolutional Neural Nets; Faltning; Neurala Nätverk; Neurala Nät; Syntetisk Biologi; Alternativ Splicing; Splicing; AS; DNA; Massivt Parallellt Bibliotek; Syntetiskt DNA; Computer Sciences; Datavetenskap (datalogi)

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

APA (6th Edition):

Linder, J. (2015). Modeling the intronic regulation of Alternative Splicing using Deep Convolutional Neural Nets. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172327

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):

Linder, Johannes. “Modeling the intronic regulation of Alternative Splicing using Deep Convolutional Neural Nets.” 2015. Thesis, KTH. Accessed January 17, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172327.

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

MLA Handbook (7th Edition):

Linder, Johannes. “Modeling the intronic regulation of Alternative Splicing using Deep Convolutional Neural Nets.” 2015. Web. 17 Jan 2019.

Vancouver:

Linder J. Modeling the intronic regulation of Alternative Splicing using Deep Convolutional Neural Nets. [Internet] [Thesis]. KTH; 2015. [cited 2019 Jan 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172327.

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

Council of Science Editors:

Linder J. Modeling the intronic regulation of Alternative Splicing using Deep Convolutional Neural Nets. [Thesis]. KTH; 2015. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172327

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


Indian Institute of Science

12. Srinivas, Kruthiventi S S. Visual Flow Analysis and Saliency Prediction.

Degree: 2016, Indian Institute of Science

 Nowadays, we have millions of cameras in public places such as traffic junctions, railway stations etc., and capturing video data round the clock. This humongous… (more)

Subjects/Keywords: Visual Flow Analysis; Saliency Prediction; Visual Saliency; Static Flow Analysis; Surveillance Videos; Dynamic Flow Analysis; DeepFix; Convolutional Network; Eye Fixation Prediction; Salient Object Segmentation; Convolutional Neural Networks (CNNs); Saliency Unified; Computational and Data Sciences

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

APA (6th Edition):

Srinivas, K. S. S. (2016). Visual Flow Analysis and Saliency Prediction. (Thesis). Indian Institute of Science. Retrieved from http://etd.iisc.ernet.in/handle/2005/2930 ; http://etd.ncsi.iisc.ernet.in/abstracts/3792/G27785-Abs.pdf

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):

Srinivas, Kruthiventi S S. “Visual Flow Analysis and Saliency Prediction.” 2016. Thesis, Indian Institute of Science. Accessed January 17, 2019. http://etd.iisc.ernet.in/handle/2005/2930 ; http://etd.ncsi.iisc.ernet.in/abstracts/3792/G27785-Abs.pdf.

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

MLA Handbook (7th Edition):

Srinivas, Kruthiventi S S. “Visual Flow Analysis and Saliency Prediction.” 2016. Web. 17 Jan 2019.

Vancouver:

Srinivas KSS. Visual Flow Analysis and Saliency Prediction. [Internet] [Thesis]. Indian Institute of Science; 2016. [cited 2019 Jan 17]. Available from: http://etd.iisc.ernet.in/handle/2005/2930 ; http://etd.ncsi.iisc.ernet.in/abstracts/3792/G27785-Abs.pdf.

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

Council of Science Editors:

Srinivas KSS. Visual Flow Analysis and Saliency Prediction. [Thesis]. Indian Institute of Science; 2016. Available from: http://etd.iisc.ernet.in/handle/2005/2930 ; http://etd.ncsi.iisc.ernet.in/abstracts/3792/G27785-Abs.pdf

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


Indian Institute of Science

13. Srinivas, Kruthiventi S S. Visual Flow Analysis and Saliency Prediction.

Degree: 2016, Indian Institute of Science

 Nowadays, we have millions of cameras in public places such as traffic junctions, railway stations etc., and capturing video data round the clock. This humongous… (more)

Subjects/Keywords: Visual Flow Analysis; Saliency Prediction; Visual Saliency; Static Flow Analysis; Surveillance Videos; Dynamic Flow Analysis; DeepFix; Convolutional Network; Eye Fixation Prediction; Salient Object Segmentation; Convolutional Neural Networks (CNNs); Saliency Unified; Computational and Data Sciences

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

APA (6th Edition):

Srinivas, K. S. S. (2016). Visual Flow Analysis and Saliency Prediction. (Thesis). Indian Institute of Science. Retrieved from http://hdl.handle.net/2005/2930

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):

Srinivas, Kruthiventi S S. “Visual Flow Analysis and Saliency Prediction.” 2016. Thesis, Indian Institute of Science. Accessed January 17, 2019. http://hdl.handle.net/2005/2930.

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

MLA Handbook (7th Edition):

Srinivas, Kruthiventi S S. “Visual Flow Analysis and Saliency Prediction.” 2016. Web. 17 Jan 2019.

Vancouver:

Srinivas KSS. Visual Flow Analysis and Saliency Prediction. [Internet] [Thesis]. Indian Institute of Science; 2016. [cited 2019 Jan 17]. Available from: http://hdl.handle.net/2005/2930.

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

Council of Science Editors:

Srinivas KSS. Visual Flow Analysis and Saliency Prediction. [Thesis]. Indian Institute of Science; 2016. Available from: http://hdl.handle.net/2005/2930

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


University of Technology, Sydney

14. Ding, Changxing. Robust face recognition.

Degree: 2016, University of Technology, Sydney

 Face recognition is one of the most important and promising biometric techniques. In face recognition, a similarity score is automatically calculated between face images to… (more)

Subjects/Keywords: Face recognition .; Face recognition algorithms.; Dual-Cross Patterns (DCP).; Multi-Directional Multi-Level Dual-Cross Patterns (MDML-DCPs).; Multimodal Deep Face Representation (MM-DFR).; Convolutional neural networks (CNNs).; Pose-invariant face recognition (PIFR) framework.; Patch-based face representation scheme.; Trunk-Branch Ensemble CNN (TBE-CNN).; Video-based face recognition (VFR).

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

APA (6th Edition):

Ding, C. (2016). Robust face recognition. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/52706

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):

Ding, Changxing. “Robust face recognition.” 2016. Thesis, University of Technology, Sydney. Accessed January 17, 2019. http://hdl.handle.net/10453/52706.

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

MLA Handbook (7th Edition):

Ding, Changxing. “Robust face recognition.” 2016. Web. 17 Jan 2019.

Vancouver:

Ding C. Robust face recognition. [Internet] [Thesis]. University of Technology, Sydney; 2016. [cited 2019 Jan 17]. Available from: http://hdl.handle.net/10453/52706.

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

Council of Science Editors:

Ding C. Robust face recognition. [Thesis]. University of Technology, Sydney; 2016. Available from: http://hdl.handle.net/10453/52706

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


Universitat Pompeu Fabra

15. Gong, Rong. Automatic assessment of singing voice pronunciation: a case study with Jingju music.

Degree: Departament de Tecnologies de la Informació i les Comunicacions, 2018, Universitat Pompeu Fabra

 El aprendizaje en línea ha cambiado notablemente la educación musical en la pasada década. Una cada vez mayor cantidad de estudiantes de interpretación musical participan… (more)

Subjects/Keywords: MIR; Music information retrieval; CompMusic; Data-driven; Computational model; Singing voice; Automatic assessment; Jingju; Beijing opera; Pronunciation; Syllable and phoneme segmentation; Mispronunciation detection; Pronunciation similarity; Deep learning; Neural networks; CNNs; RNNs; Siamese networks; Acoustic embedding,; Hidden Markov model; HMM; HSMM; Recuperación de información musical; Modelo computacional basado en datos; Voz de canto; Eevaluación automática; Pronunciación; Segmentación de sílabas y fonemas; Detección de falsa pronunciación; Similitud de pronunciación; Aprendizaje profundo; Redes neuronales; Redes neuronales recurrentes; Incrustación acústica; Modelo oculto de Markov; 62

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

APA (6th Edition):

Gong, R. (2018). Automatic assessment of singing voice pronunciation: a case study with Jingju music. (Thesis). Universitat Pompeu Fabra. Retrieved from http://hdl.handle.net/10803/664421

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):

Gong, Rong. “Automatic assessment of singing voice pronunciation: a case study with Jingju music.” 2018. Thesis, Universitat Pompeu Fabra. Accessed January 17, 2019. http://hdl.handle.net/10803/664421.

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

MLA Handbook (7th Edition):

Gong, Rong. “Automatic assessment of singing voice pronunciation: a case study with Jingju music.” 2018. Web. 17 Jan 2019.

Vancouver:

Gong R. Automatic assessment of singing voice pronunciation: a case study with Jingju music. [Internet] [Thesis]. Universitat Pompeu Fabra; 2018. [cited 2019 Jan 17]. Available from: http://hdl.handle.net/10803/664421.

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

Council of Science Editors:

Gong R. Automatic assessment of singing voice pronunciation: a case study with Jingju music. [Thesis]. Universitat Pompeu Fabra; 2018. Available from: http://hdl.handle.net/10803/664421

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

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