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Visual Object Tracking Using Deep Learning

Inglese · Copertina rigida

Spedizione di solito entro 1 a 3 settimane

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The text comprehensively discusses tracking architecture under stochastic and deterministic frameworks and presents experimental results under each framework with qualitative and quantitative analysis. It covers deep learning techniques for feature extraction, template matching, and training the networks in tracking algorithms.


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Dr. Ashish Kumar, Ph.D., is working as an assistant professor with Bennett University, Greater Noida, U.P., India. He has completed his Ph.D. in Computer Science and Engineering from Delhi Technological University (formerly DCE), New Delhi, India in 2020. He has received best researcher award from the Delhi Technological University for his contribution in the computer vision domain. He has completed M.Tech with distinction in computer Science and Engineering from GGS Inderpratha University, New Delhi. He has published many research papers in various reputed national and international journals and conferences. His current research interests include object tracking, image processing, artificial intelligence, and medical imaging analysis.


Riassunto

The text comprehensively discusses tracking architecture under stochastic and deterministic frameworks and presents experimental results under each framework with qualitative and quantitative analysis. It covers deep learning techniques for feature extraction, template matching, and training the networks in tracking algorithms.

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