Papers

Amit, Y. and Walker J., `Recurrent network of perceptrons with three state synapses achieves competitive classification on real inputs', Frontiers in Computational Neuroscience, (2012).

Hatsopoulos, N. G., and Amit, Y. `Synthesizing complex movement fragment representations from motor cortical ensembles.' J. of Physiology, Paris, (2012).

Saleh, M., Kazutuka, T., Amit Y. and Hatsopoulos, N. G. (2010) `Encoding of Coordinated Grasp Trajectories in Primary Motor Cortex', The Journal of Neuroscience, (2011).

Huang, Y. and Amit, Y., Capacity Analysis in Multi-state Synaptic Models: a Retrieval Probability Perspective. Journal of Computational Neurosience. (2011)

Amit, Y. and Huang Y., Precise capacity analysis in binary networks with multiple coding level inputs. Neural Computation, vol 22. no 3. (2010)

Dickey, A. S., Suminski, A., Amit, Y. and Hatsopoulos, N. G., `Single-unit stability using chronically implanted multi-electrode arrays.' J Neurophysiol (2009).

Romani, S., Amit D. J., and Amit, Y. Optimizing one-shot learning with binary synapses. Neural Computation, vol. 20. (2008).

Cortes, L. and Amit, Y. Efficient detection and tracking of multiple vesicles in video microscopy, IEEE PAMI (Special issue: Real World Image Annotation and Retrieval), vol. 30 (2008).

Hatsopoulos, N. G., Xu, Q. and Amit, Y. `Encoding of movement fragments in the motor cortex.' Journal of Neuroscience, (2007).

Amit, Y. and Trouvé, A. Generative Models for Labeling Multi-Object Configurations in Images. Lecture Notes in Computer Science, Volume 4170, Springer. (2007)

Allassonniere, S, Amit, Y. and Trouvé, A. Toward a Coherent Statistical Framework for Dense Deformable Template Estimation. JRSS (Series B) (2007)

Amit, Y. and Trouvé, A. POP: Patchwork of Parts Models for Object Recognition. IJCV Vol. 75 (2007)

Bernstein, E. and Amit, Y., Statistical Models for Object Classification and Detection. CVPR (2005)

Amit, Y., Geman, D. and Fan, X., A Coarse-to-Fine strategy for Multi-class Shape Detection. IEEE-PAMI (2004).

Krempp, S., Geman, D. and Amit, Y. Sequential Learning of Reusable Parts for Object Detection. (2002)

Amit, Y. and Mascaro, M., An integrated network for invariant visual detection and recognition. Vision Research, (2003).

Amit, Y., Koloydenko, A. and Niyogi, P., Robust acoustic object detection. (2002).

Amit, Y. and Gilles Blanchard, Multiple randomized classifiers: MRCL, (2001).

Amit, Y. and Mascaro, M., Attractor networks for shape recognition. Neural Computation, (2001). .

Amit, Y. and Murua, A., Speech recognition using randomized relational decision trees. IEEE Transactions on Speech and Audio Processing, (2001).

Amit, Y, A neural network architecture for visual selection. Neural Computation, (2000). Click here to get the images.

Amit, Y. and Geman, D., A computational model for visual selection. Neural Computation, (1998)

Amit, Y., Deformable Templates for Object Detection. Notes for a tutorial presented at ICIP 1998.

Amit, Y., Geman, D. and Jedynak, B., Efficient focusing and face detection, in Face Recognition: From Theory to Applications, eds. H. Wechsler et al, NATO ASI Series F, Springer Verlag, Berlin, (1997).

Amit, Y., Geman D. and Wilder, K., Joint induction of shape features and tree classifiers, IEEE PAMI, (1997).

Amit, Y. and Geman, D. Shape quantization and recognition with randomized trees, Neural Computation (1997).

Amit, Y., Graphical shape templates for automatic anatomy detection with applications to MRI brain scans, IEEE MI (1997).

Amit, Y. and Kong, A., Graphical templates for model registration, IEEE PAMI (1996).

Amit, Y. and Geman, D. Randomized Inquiries about shape; an application to handwritten digit recognition, (1994).

Amit, Y. A non-linear variational problem for image matching, SIAM Journal on Scientific Computing, (1994).

Amit, Y. and Manbeck, K., Deformable template models for emission tomography, IEEE MI (1993).

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