http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Deep Learning in Object Detection and Recognition
XVI, 224 p. 113 illus., 92 illus. in color. online resource.
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.
1. An Overview of Deep Learning -- 2. Object Detection In Deep Learning -- 3. Deep Learning in Face Recognition across Pose and Illumination -- 4. Face Anti-spoofing via Deep Local Binary Pattern -- 5. Face Anti-spoofing via Deep Local Binary Pattern -- 6. Deep Learning Architectures for Face Recognition in Video Surveillance -- 7. Deep learning for 3D data -- 8. Deep Learning based Descriptors for Object Instance Search.
edited by Xiaoyue Jiang, Abdenour Hadid, Yanwei Pang, Eric Granger, Xiaoyi Feng.