{"product_id":"9780792373483","title":"The Springer International Series in Engineering and Computer Science","description":"\u003ch1\u003eThe Springer International Series in Engineering and Computer Science\u003c\/h1\u003e \u003ch2\u003eBartlett, Marian Stewart\u003c\/h2\u003e \u003cp\u003e\u003cem\u003eFace Image Analysis by Unsupervised Learning\u003c\/em\u003e explores  adaptive approaches to image analysis. It draws upon principles of  unsupervised learning and information theory to adapt processing to  the immediate task environment. In contrast to more traditional  approaches to image analysis in which relevant structure is determined  in advance and extracted using hand-engineered techniques, \u003cem\u003eFace  Image Analysis by\u003c\/em\u003e \u003cem\u003eUnsupervised Learning\u003c\/em\u003e explores methods that  have roots in biological vision and\/or learn about the image structure  directly from the image ensemble. Particular attention is paid to  unsupervised learning techniques for encoding the statistical  dependencies in the image ensemble. \u003cbr\u003e  The first part of this volume reviews unsupervised learning,  information theory, independent component analysis, and their relation  to biological vision. Next, a face image representation using  independent component analysis (ICA) is developed, which is an  unsupervised learning technique based on optimal information transfer  between neurons. The ICA representation is compared to a number of  other face representations including eigenfaces and Gabor wavelets on  tasks of identity recognition and expression analysis. Finally,  methods for learning features that are robust to changes in viewpoint  and lighting are presented. These studies provide evidence that  encoding input dependencies through unsupervised learning is an  effective strategy for face recognition. \u003cbr\u003e  \u003cem\u003eFace Image Analysis by Unsupervised Learning\u003c\/em\u003e is suitable as a  secondary text for a graduate-level course, and as a reference for  researchers and practitioners in industry.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2001-06-30\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9780792373483\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4615-1637-8\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 173\u003c\/p\u003e ","brand":"Springer US","offers":[{"title":"Default Title","offer_id":45578397810828,"sku":"9780792373483","price":98.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780792373483.jpg?v=1770781968","url":"https:\/\/lateknightbooks.com\/products\/9780792373483","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}