Deep Learning in Object Detection and Recognition

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Jiang, Xiaoyue (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Hadid, Abdenour (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Pang, Yanwei (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Granger, Eric (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Feng, Xiaoyi (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Θέματα: Optical data processing.; Data mining.; Pattern recognition.; Image Processing and Computer Vision.; Data Mining and Knowledge Discovery.; Pattern Recognition.
• Φυσική περιγραφή: XVI, 224 p. 113 illus., 92 illus. in color. online resource.
• ISBN: 9789811051524
• DOI: 10.1007/978-981-10-5152-4

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.