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| Resources |
| Source
code |
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[Biologically
motivated framework for object recognition] We
have developped a computational theory of object recognition
in the cortex. We have extensively compared the tuning
properties of the units in the model to those of cortical
cells. The model is qualitatively
and quantitatively consistent with several properties
of subpopulations of cells in V1, V4, IT, and PFC as
well as fMRI and psychophysical data.
The model has
evolved over the past few years and we have made
several software implementations available.
>> Download
web page.
[Biologically motivated framework
for action recognition] We have recently extended
our work on object recognition to the recognition of actions
with a model of the dorsal based on a dictionary of
position and scale invariant spatio-temporal motion features.
>> Source code. |
| Supplementary web material |
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[T.
Serre, A. Oliva and T. Poggio. A feedforward architecture
accounts for rapid categorization. Proceedings of
the National Academy of Science, 104(15), pp. 6424-6429,
April 2007 open
access ] The supplementary
web material accompanies the study and includes,
in particular, a basic software implementation of
the computational model and the animal vs. non-animal
stimulus database (along with the performance of
benchmark systems). It also includes a summary of
various performance measures for both human observers
and the model (including ROC analysis, error and
hit rates) as well as reaction times for human observers.
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[T.
Serre, L. Wolf, S. Bileschi, M. Riesenhuber and T.
Poggio. Object recognition with ortex-like mechanisms.
In: IEEE Transactions on Pattern Analysis and Machine
Intelligence, 29 (3), pp. 411-426 , 2007] Here
is a link to
the software implementation to the model of the ventral
stream of the visual cortex used in this study. We
used the Street-scene
database collected by Stan Bileschi (CBCL, MIT)
to benchmark the system. We also used some the CalTech-6 and CalTech-101 datasets.
In
this study we used osusvm,
the matlab interface for libsvm.
Here is a list of SVM software implementations and
general machine learning toolboxes that are publicly
available.
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| SVM
software implementations and general machine learning
toolboxes |
[General
machine learning toolboxes] [matlab] Spider <Max
Planck Institute for Biol. Cybernetics> / STPRtool
toolbox <Czech Technical University in Prague> / Regularization
tools <Technical University of Denmark>
[SVM software][C] libsvm / svmlight /
svmFu (no
longer supported)
[SVM software][matlab
interfaces] osusv (libsvm) /
Tom
Briggs (svmlight) / Anton
Schwaighofer (svmlight) |
| Image
datasets |
CBCL
street scene database (created
by Stan Bileschi)
Other CBCL
image datasets
Misc
image
databases:
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