Computer Vision - CCF Chinese Conference, CCCV 2015, Xi'an, China, September 18-20, 2015, Proceedings, Part II

The two volumes CCIS 546 and 547 constitute the refereed proceedings of the CCF Chinese Conference on Computer Vision, CCCV 2015, held in Xi'an, China, in September 2015.
The total of 89 revised full papers presented in both volumes were carefully reviewed and selected from 176 submissions. The papers address issues such as computer vision, machine learning, pattern recognition, target recognition, object detection, target tracking, image segmentation, image restoration, face recognition, image classification.

Sommario

Computer vision.- Machine learning.- Pattern recognition.- Target recognition.-Object detection.- Target tracking.- Image segmentation.- Image restoration.-Face recognition.- Image classification.

Dettagli sul prodotto

• Con la collaborazione di: Xili Chen (Editore), Xilin Chen (Editore), Qiguang Miao (Editore), Liang Wang (Editore), Liang Wang et al (Editore), Hongbin Zha (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 01.01.2015
• EAN: 9783662485699
• ISBN: 978-3-662-48569-9
• Pagine: 472
• Dimensioni: 157 mm x 239 mm x 25 mm
• Peso: 739 g
• Illustrazioni: XX, 472 p. 231 illus.
• Serie: Communications in Computer and Information Science; Communications in Computer and Information Science
• Categorie: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Software applicativo; C, Künstliche Intelligenz, machine learning, Artificial Intelligence, Mustererkennung, computer science, Computer Vision, Image Processing and Computer Vision, pattern recognition, Automated Pattern Recognition, Optical data processing, Feature Extraction, image segmentation, neural network, image registration, image filtering, denoising, event detection, image classification, quality assessment, image restoration, Super-resolution, image search, face verification, image mosaic, online boosting, texture synthesis, saliency detection, feature matching, feature coding