Visual object tracking using deep learning / Ashish Kumar.
"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 t...
Saved in:
| Online Access: |
Full Text (via Taylor & Francis) |
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| Main Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boca Raton :
CRC Press, Taylor & Francis Group,
2024.
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| Edition: | First edition. |
| Subjects: |
| Summary: | "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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| Physical Description: | 1 online resource |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781003456322 1003456324 |
| Source of Description, Etc. Note: | Description based on print version record and CIP data provided by publisher. |
| Biographical or Historical Data: | 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. |