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John Allman

dblp:52/6954 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1991
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Hardware accelerators and domain-specific architectures · 100%
Computer graphics and multimedia
1 paper
Computational photography and imaging · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware accelerators and domain-specific architectures
neural network hardware
0.011990
A VLSI Neural Network for Color Constancy · NIPS 1990
Hardware accelerators and domain-specific architectures › neural network hardware
VLSI neural network
0.011990
A VLSI Neural Network for Color Constancy · NIPS 1990
Computational photography and imaging
color constancy
0.011990
A VLSI Neural Network for Color Constancy · NIPS 1990

Methods — techniques the papers use, named apart from their topics

neural network · 0.0VLSI · 0.0
YearPublicationVenuePosition
1991 A real-time neural system for color constancy
abstract
A neural network approach to the problem of color constancy is presented. Various algorithms based on Land's retinex theory are discussed with respect to neurobiological parallels, computational efficiency, and suitability for VLSI implementation. The efficiency of one algorithm is improved by the application of resistive grids and is tested in computer simulations; the simulations make clear the strengths and weaknesses of the algorithm. A novel extension to the algorithm is developed to address its weaknesses. An electronic system that is based on the original algorithm and that operates at video rates was built using subthreshold analog CMOS VLSI resistive grids. The system displays color constancy abilities and qualitatively mimics aspects of human color perception.
John Allman, Rodney M. Goodman
IEEE Trans. Neural Networks2
1990 A VLSI Neural Network for Color Constancy
John Allman, Geoffrey C. Fox, Rodney M. Goodman
NIPS2