000			03411nam a22004935i 4500
001			978-0-387-23469-4
003			DE-He213
005			20161121230647.0
007			cr nn 008mamaa
008			100301s2005 xxu| s |||| 0|eng d
020			_a9780387234694 _9978-0-387-23469-4
024	7		_a10.1007/b101575 _2doi
050		4	_aRC321-580
072		7	_aPSAN _2bicssc
072		7	_aMED057000 _2bisacsh
082	0	4	_a612.8 _223
100	1		_aRasche, Christoph. _eauthor.
245	1	4	_aThe Making of a Neuromorphic Visual System _h[electronic resource] / _cby Christoph Rasche.
264		1	_aBoston, MA : _bSpringer US, _c2005.
300			_aXI, 140 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aSeeing: Blazing Processing Characteristics -- Category Representation and Recognition Evolvement -- Neuroscientific Inspiration -- Neuromorphic Tools -- Insight From Line Drawings Studies -- Retina Circuits Signaling and Propagating Contours -- The Symmetric-Axis Transform -- Motion Detection -- Neuromorphic Architectures: Pieces and Proposals -- Shape Recognition with Contour Propagation Fields -- Scene Recognition -- Summary.
520			_aThe 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.
650		0	_aMedicine.
650		0	_aNeurosciences.
650		0	_aNeurobiology.
650		0	_aMicrowaves.
650		0	_aOptical engineering.
650		0	_aBiomedical engineering.
650	1	4	_aBiomedicine.
650	2	4	_aNeurosciences.
650	2	4	_aBiomedical Engineering.
650	2	4	_aNeurobiology.
650	2	4	_aMicrowaves, RF and Optical Engineering.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387234687
856	4	0	_uhttp://dx.doi.org/10.1007/b101575
912			_aZDB-2-SBL
950			_aBiomedical and Life Sciences (Springer-11642)
999			_c502074 _d502074