Deep Learning in Object Detection and Recognition |
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| Editor:
| Jiang, Xiaoyue
Hadid, Abdenour
Pang, Yanwei
Granger, Eric
Feng, Xiaoyi |
| ISBN: | 978-981-10-5151-7 |
| Publication Date: | Nov 2019 |
| Publisher: | Springer
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| Book Format: | Hardback |
| List Price: | USD $179.99 |
Book Description:
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This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.
The book offers a...
More Description
This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.
The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.