Sussex: Wiley, 2009. - 444 p. The book Kernel Methods for Remote Sensing Data Analysis presents research related to remote sensing based on the recent advances in kernel methods. The book is organized into five parts. The first part of the book presents two background chapters on the key aspects of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. The remaining four parts address the most recent research in developing kernel methods in remote sensing for supervised classification, semi-supervised classification, regression, and feature extraction.
Чтобы скачать этот файл зарегистрируйтесь и/или войдите на сайт используя форму сверху.