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Mostrando ítems 11-16 de 16
Artículo
Exploration of spatial-temporal dynamic phenomena in a 32×32-cell stored program two-layer CNN universal machine chip prototype
(World Scientific Publishing, 2003)
This paper describes a full-custom mixed-signal chip that embeds digitally programmable analog parallel processing and distributed image memory on a common silicon substrate. The chip was designed and fabricated in a ...
Ponencia
3-Layer CNN Chip for Focal-Plane Complex Dynamics with Adaptive Image Capture
(Institute of Electrical and Electronics Engineers, 2006)
This paper presents a CMOS implementation of a layered CNN concurrent with 32times32 photosensors with locally programmable integration time for adaptive image capture. The network is arranged in two layers containing ...
Ponencia
A Focal-Plane Image Processor for Low Power Adaptive Capture and Analysis of the Visual Stimulus
(Institute of Electrical and Electronics Engineers, 2007)
Portable applications of artificial vision are limited by the fact that conventional processing schemes fail to meet the specifications under a tight power budget. A bio-inspired approach, based in the goal-directed ...
Ponencia
Programmable retinal dynamics in a CMOS mixed-signal array processor chip
(The International Society for Optical Engineering - SPIE, 2003)
The low-level image processing that takes place in the retina is intended to compress the relevant visual information to a manageable size. The behavior of the external layers of the biological retina has been successfully ...
Artículo
ACE16K: The Third Generation of Mixed-Signal SIMD-CNN ACE Chips Toward VSoCs
(Institute of Electrical and Electronics Engineers, 2004)
Today, with 0.18-μm technologies mature and stable enough for mixed-signal design with a large variety of CMOS compatible optical sensors available and with 0.09-μm technologies knocking at the door of designers, we can ...
Ponencia
CMOS realization of a 2-layer CNN universal machine chip
(Institute of Electrical and Electronics Engineers, 2002)
Some of the features of the biological retina can be modelled by a cellular neural network (CNN) composed of two dynamically coupled layers of locally connected elementary nonlinear processors. In order to explore the ...