publication . Part of book or chapter of book . Preprint . Other literature type . Conference object . 2016

Feedback Networks

Amir R. Zamir; Te-Lin Wu; Lin Sun; William B. Shen; Bertram E. Shi; Jitendra Malik; Silvio Savarese;
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  • Published: 30 Dec 2016
  • Publisher: Springer Berlin Heidelberg
Abstract
Currently, the most successful learning models in computer vision are based on learning successive representations followed by a decision layer. This is usually actualized through feedforward multilayer neural networks, e.g. ConvNets, where each layer forms one of such successive representations. However, an alternative that can achieve the same goal is a feedback based approach in which the representation is formed in an iterative manner based on a feedback received from previous iteration's output. We establish that a feedback based approach has several fundamental advantages over feedforward: it enables making early predictions at the query time, its output n...
Subjects
free text keywords: Computer Science - Computer Vision and Pattern Recognition
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publication . Part of book or chapter of book . Preprint . Other literature type . Conference object . 2016

Feedback Networks

Amir R. Zamir; Te-Lin Wu; Lin Sun; William B. Shen; Bertram E. Shi; Jitendra Malik; Silvio Savarese;