A Biological Model of Object Recognition with Feature Learning

Title: en_US A Biological Model of Object Recognition with Feature Learning
Creator: en_US Louie, Jennifer
Date: 2004-10-01T14:00:10Z
Date Available: 2004-10-01T14:00:10Z
Date Issued: en_US 2003-06-01
Identifier: en_US AITR-2003-009; en_US CBCL-227
uri: http://hdl.handle.net/1721.1/5571
Abstract: en_US Previous biological models of object recognition in cortex have been evaluated using idealized scenes and have hard-coded features, such as the HMAX model by Riesenhuber and Poggio [10]. Because HMAX uses the same set of features for all object classes, it does not perform well in the task of detecting a target object in clutter. This thesis presents a new model that integrates learning of object-specific features with the HMAX. The new model performs better than the standard HMAX and comparably to a computer vision system on face detection. Results from experimenting with unsupervised learning of features and the use of a biologically-plausible classifier are presented.
Extent: 4307593 bytes; 5073756 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-2003-009; en_US CBCL-227
Subject: en_US AI