PowerPoint Presentation
Computational models of invariant object recognitionSupervisor:
Dr. Reza EbrahimpourStudent: Alireza Akhavan Pour
HMAX VisNet
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4 HMAX VisNet
VIEW ON THE VISUAL PATHWAY
Visual Areas of the Human Cerebral Cortex5/31
On center
No lightLight onNo light
No lightLight onNo light
Off center
Neurons and areas in visual system 14/40VIEW ON THE VISUAL
PATHWAY
BEHAVIOR OF AN GANGLION CELL 6/31
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No lightwrong position-wrong orientationwright position-wrong
orientationwrong position-wright orientationWright positionWright
orientation
VIEW ON THE VISUAL PATHWAY, SIMPLE CORTICAL CELLS7/31
Behavior of a complex cell 8/31
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9 HMAX VisNet
Hmax Hubel Wiesel Hubel Wiesel :
( receptive field) : (feed-forward)
195910/31
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4 11/31V1-V2
V1-V2
V2-V4
V4/PIT
ITS1
C1
S2
C2
12 HMAX VisNet
13/31 :VisNet
Continuous transformation (CT) learning
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:VisNet15/31
VisNet 16/31Edmund T. Rolls
4 (local graded inhibition) (topologicall) (modified Hebbian
learning rule )V2-> V4->posterior inferior temporal ->
anterior inferior temporal
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67%
128*128
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Architecture17/31
1 V1
input18/31
Input to layer 1
. - - 1
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I .
4- .
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4 3 2 191889899.2267540190
contrast enhancement (contrast enhancement) 0 1
:r ( ) : y : ( !) : activation
sparseness21/31
(trace learning rule) :
0.5 .22/31
xj j- y t y t wj j- trace value ( )
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Neural-like models via performance optimizationD. . L. K.
Yamins, H. Hong, C. F. Cadieu, E. A. Solomon, D. Seibert and J. J.
DiCarlo, "Performance-optimized hierarchical models predict neural
responses in higher visual cortex," Proceedings of the National
Academy of Sciences, p. 201403112, 2014. 25/31
VisNet Hmax
VisnetHmaxtesttesttraintrain26/31
27 HMAX VisNet
invariency (re-train) GPU Spike 28/31
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29References
E. Rolls, " Invariant visual object and face recognition: neural
and computational bases, and a model," In Computational
Neuroscience, vol. 51, pp. 167194, 2012.
T. Rolls, E.T., and Stringer, "Continuous transformation
learning of translation invariant representations," Exp.BainRes,
pp. 255270, 2010.
D. L. K. Yamins, H. Hong, C. F. Cadieu, E. A. Solomon, D.
Seibert and J. J. DiCarlo, "Performance-optimized hierarchical
models predict neural responses in higher visual cortex,"
Proceedings of the National Academy of Sciences, p. 201403112,
2014.
M. Riesenhuber and T. Poggio, "Hierarchical Models of Object
Recognition in Cortex," Nature Neuroscience, vol. 2, no. 11, pp.
1019-1025, 1999.
Stringer, S. M. and E. T. Rolls. 2008. Learning transform
invariant object recognition in the visual system withmultiple
stimuli present during training, Neural Networks 21:888-903
REFERENCES30/31
[1] E. a. T. Rolls, " Processing speed in the cerebral cortex
and the neurophysiology of visual masking.
Proc.R.Soc.Lond.BBiol.Sci. 257, 915.," 1994.
[2] S. S. P. a. N. R. Hestrin, "Mechanisms generating the time
course of dual component exci tatory synaptic currents recorded in
hippocampal slices.," Neuron 5, 1990
[3] P. G. J. a. E. m. G. Montague, "Spatial signalling in the
development and function of neural connections," Cereb.Cortex 1,
199220.REFERENCES31/31
