A Neural Computation Model Based on nCRF and Reverse Control Mechanism
- 509 Downloads
Previous nCRF models are mainly based on fixed RF whose dynamic characteristics are not taken into account. In this paper, we establish a multilayer neural computation model with feedback for the basic structure of nCRF. In our model, GC’s RF can dynamically and self-adaptively adjust its size according to stimulus properties. RF becomes smaller in local areas where the image details need distinguishing and larger where the image information have no obvious difference. The experimental results fully reflect the dynamic characteristics of GC’s RF. Among adjacent areas in an image, similar ones are integrated together and represented by a larger RF, while dissimilar ones are separated and represented by several smaller RFs. Such a biology-inspired neural computation model is a reliable approach for image segmentation and clustering integration.
KeywordsNon-classical receptive field Neural network Image representation
Unable to display preview. Download preview PDF.
- 1.Ikeda, H., Wright, M.J.: The outer disinhibitory surround of the retinal ganglion cell receptive field. J. Physiol. 226, 511–544 (1972)Google Scholar
- 2.Krüger, J., Fischer, B.: Strong periphery effect in cat retinal ganglion cells. Excitatory responses in ON- and OFF-center neurons to single grid displacements. Exp. Brain Res. 18, 316–318 (1973)Google Scholar
- 3.Sun, C.: Spatial Property of Extraclassical Receptive Field of the Relay Cells in Cat’s Dorsal Lateral Geniculate Nucleus and its Interaction with the Classical Receptive Field. PhD thesis, Fudan University (2004)Google Scholar
- 5.Li, Z., et al.: A New Computational Model of Retinal Ganglion Cell Receptive Fields- I. a Model of Ganglion Cell Receptive Fields with Extended Disinhibitory Area. Acta Biophysica Sinica 16, 288–295 (2000)Google Scholar
- 7.Qiu, F.T., Li, C.Y.: Mathematical simulation of disinhibitory properties of concentric receptive field. Acta Biophysica Sinica 11, 214–220 (1995)Google Scholar
- 8.Li, C.Y.: New Advances in Neuronal Mechanisms of Image Information Processing. Bulletin of National Natural Science Foundation of China 3, 201–204 (1997)Google Scholar
- 10.Shou, T.D.: Brain mechanisms of Visual Information Processing. Shanghai Scientific & Technological Education Publishing House, Shanghai (1997)Google Scholar
- 11.Yang, X.L., Tornqvist, K., Dowling, J.E.: Modulation of cone horizontal cell activity in the teleost fish retina. II. Role of interplexiform cells and dopamine in regulating light responsiveness. J. Neurosci. 8, 2259–2268 (1988)Google Scholar