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Object Detection with Deep Learning Models 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. Features: A structured overview of deep
learning in object detection A diversified collection of
applications of object detection using deep neural networks
Emphasize agriculture and remote sensing domains Exclusive
discussion on moving object detection
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