A model of object recognition
Our model of object recognition [1, 2] puts together many known and accepted ideas about the neurophysiology of the visual cortex, and tries to provide a unified framework for understanding the visual information processing.
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New Matlab source code (Summer 2006)
Here is an improved version of the software, which incoporates learned features, biologically plausible operations (normalized dot products and soft-max, replacing Gaussian and max), and more layers (bypass routes and more intermediate layers). Mex-C routine is used to speed up the computation (a full computation of 256x256 image would take about one minute on a regular PC).
- Download ModelObjRecog_Ver5.3.tar.gz.
- Untar it (tar -zxvf ModelObjectRecog_Ver5.3.tar.gz).
- Read README.txt about information on how to run.
- Start MATLAB.
- Look at and try the enclosed sample files.
- Thomas Serre's version: Unsupervised feature learning from natural images 
- Jim Mutch's version: Multiscale Feature Hierarchy Library
- Collection in CBCL's website
 M. Riesenhuber and T. Poggio. "Hierarchical Models of Object Recognition in Cortex" in Nature Neuroscience: 2, 1019-1025, 1999.
 T. Serre, M. Kouh, C. Cadieu, U. Knoblich, G. Kreiman and T. Poggio. "A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex" in CBCL Paper #259/AI Memo #2005-036, Massachusetts Institute of Technology, Cambridge, MA, 2005.
 T. Serre, J. Louie, M. Riesenhuber and T. Poggio. "On the Role of Object-specific Features for Real World Object Recognition in Biological Vision" in Workshop on Biologically Motivated Computer Vision (BMCV), 2002.
Last modified: June, 2006.