Learning Representation for Multi-View Data Analysis: Models and ApplicationsКНИГИ » ПРОГРАММИНГ
Название: Learning Representation for Multi-View Data Analysis: Models and Applications Автор: Zhengming Ding Издательство: Springer Год: 2019 Страниц: 268 Формат: PDF, EPUB Размер: 37 Mb Язык: English
This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal.
A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.
Multi-Sensor Image Fusion and Its Applications Название: Multi-Sensor Image Fusion and Its Applications Автор: Edited by Rick S. Blum and Zheng Liu Издательство: Taylor & Francis Group Год:...
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Learning Representation for Multi-View Data Analysis: Models and Applications 
