TY - BOOK ID - 206881 TI - The making of a neuromorphic visual system PY - 2005 SN - 128014775X 9786610147755 0387234691 0387234683 146149849X PB - New York : Springer, DB - UniCat KW - Neural networks (Computer science) KW - Visual pathways. KW - Integrated circuits KW - Design and construction. KW - Visual system KW - Afferent pathways KW - Vision KW - Artificial neural networks KW - Nets, Neural (Computer science) KW - Networks, Neural (Computer science) KW - Neural nets (Computer science) KW - Artificial intelligence KW - Natural computation KW - Soft computing KW - Neurosciences. KW - Biomedical engineering. KW - Neurobiology. KW - Microwaves. KW - Biomedical Engineering and Bioengineering. KW - Microwaves, RF and Optical Engineering. KW - Hertzian waves KW - Electric waves KW - Electromagnetic waves KW - Geomagnetic micropulsations KW - Radio waves KW - Shortwave radio KW - Clinical engineering KW - Medical engineering KW - Bioengineering KW - Biophysics KW - Engineering KW - Medicine KW - Neural sciences KW - Neurological sciences KW - Neuroscience KW - Medical sciences KW - Nervous system KW - Neurosciences KW - Optical engineering. KW - Mechanical engineering UR - https://www.unicat.be/uniCat?func=search&query=sysid:206881 AB - The reader is presented an approach to the construction of a visual system, which is behaviorally, computationally and neurally motivated. The central goal is to characterize the process of visual categorization and to find a suitable representation format that can successfully deal with the structural variability existent within visual categories. It does not define such representations a priori but attempts to show directions on how to gradually work towards them. The book reviews past and existent theories of visual object and shape recognition in the fields of computer vision, neuroscience and psychology. The entire range of computations is discussed, as for example contour extraction in retinal circuits, orientation determination in cortical networks, position and scale independence of shape, as well as the issue of object and shape representation in a neural substrate. Region-based approaches are discussed and are modeled with wave-propagating networks. It is demonstrated how those networks operate on gray-scale images. A completely novel shape recognition architecture is proposed that can recognize simple shapes under various degraded conditions. It is discussed how such networks can be used for constructing basic-level object representations. It is envisioned how those networks can be implemented using the method of neuromorphic engineering, an analog electronic hardware substrate than can run neural computations in real-time and with little power. ER -