Structural, Syntactic, and Statistical Pattern Recognition Joint IAPR International Workshop, S+SSPR 2018, Beijing, China, August 17-19, 2018, Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Bai, Xiao (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Hancock, Edwin R. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Ho, Tin Kam (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Wilson, Richard C. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Biggio, Battista (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Robles-Kelly, Antonio (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11004
• Θέματα: Artificial intelligence.; Pattern recognition.; Optical data processing.; Algorithms.; Computer science-Mathematics.; Data structures (Computer science).; Artificial Intelligence.; Pattern Recognition.; Image Processing and Computer Vision.; Algorithm Analysis and Problem Complexity.; Discrete Mathematics in Computer Science.; Data Structures.
• Φυσική περιγραφή: XIII, 524 p. 134 illus. online resource.
• ISBN: 9783319977850
• DOI: 10.1007/978-3-319-97785-0

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018. The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods. .