Next: About this document
Up: A Self-Organizing Neural Network
Previous: Acknowledgements
References
- 1
-
J. S. Albus.
Outline for a theory of intelligence.
IEEE Transactions on Systems, Man, and Cybernetics 21:473--509, 1991.
- 2
-
S. M. Anstis.
and Vilayanur S. Ramachandran
Entrained path deflection in apparent motion.
Vision Research 26:1731--1739, 1986.
- 3
-
S. R. Bodnarenko and L. M. Chalupa.
Stratification of On and Off ganglion cell dendrites depends on glutamate-mediated afferent activity in the developing retina.
Nature 364:144--146, 1993.
- 4
-
B. J. Frost.
Time to collision sensitive neurons in nucleus rotundus of pigeons.
Conference talk, Workshop on Binocular Stereopsis and Optic Flow, York University, Toronto, Canada, 1993.
- 5
-
S. Grossberg.
A solution of the figure-ground problem for biological vision.
Neural Networks 6:463--483, 1993.
- 6
-
G. A. Kaplan.
Kinetic disruption of optical texture: The perception of depth at an edge.
Perception & Psychophysics 6:193--198, 1969.
- 7
-
J. A. Marshall.
Self-organizing neural network architectures for computing visual depth from motion parallax.
Proceedings of the International Joint Conference on Neural Networks, Washington DC, II:227--234, 1989.
- 8
-
J. A. Marshall.
Self-organizing neural networks for perception of visual motion.
Neural Networks 3:45--74, 1990.
- 9
-
J. A. Marshall.
Challenges of vision theory: Self-organization of neural mechanisms for stable steering of object-grouping data in visual motion perception.
In S.-S. Chen, editor, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, Proceedings of the SPIE 1569, San Diego, CA, 200--215, 1991.
- 10
-
J. A. Marshall.
Unsupervised learning of contextual constraints in neural networks for simultaneous visual processing of multiple objects.
In S.-S. Chen, editor, Neural and Stochastic Methods in Image and Signal Processing, Proceedings of the SPIE 1766, San Diego, CA, 84--93, 1992.
- 11
-
J. A. Marshall.
Adaptive perceptual pattern recognition by self-organizing neural networks: Context, uncertainty, multiplicity,and scale.
Neural Networks 8:335--362, 1995.
- 12
-
K. Nakayama and S. Shimojo.
Experiencing and perceiving visual surfaces.
Science, 257:1357--1363, 1992.
- 13
-
K. Nakayama, S. Shimojo, and G. H. Silverman.
Stereoscopic depth: Its relation to image segmentation, grouping, and the recognition of occluded objects.
Perception 18:55--68, 1989.
- 14
-
V. S. Ramachandran, V. Inada, and G. Kiama.
Perception of illusory occlusion in apparent motion.
Vision Research 26:1741--1749, 1986.
- 15
-
S. Shimojo, G. H. Silverman, and K. Nakayama.
An occlusion-related mechanism of depth perception based on motion and interocular sequence.
Nature 333:265--268, 1988.
- 16
-
S. Shimojo, G. H. Silverman, and K. Nakayama.
Occlusion and the solution to the aperture problem for motion.
Vision Research 29:619--626, 1989.
- 17
-
A. Yonas, L. G. Craton, and W. B. Thompson.
Relative motion: Kinetic information for the order of depth at an edge.
Perception & Psychophysics 41:53--59, 1987.
Next: About this document
Up: A Self-Organizing Neural Network
Previous: Acknowledgements