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Andrew Izatt

dblp:62/4024 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none

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

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

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
Parallel and multicore computing · 61% Embedded and real-time systems · 30% Processor architecture and microarchitecture · 9%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing › parallel architecture
MIMD architecture		 0.011996
An MIMD Computing Platform for a Hierarchical Foveal Machine Vision System · CVPR 1996
Embedded and real-time systems › real-time signal processing
real-time image processing		 0.011996
An MIMD Computing Platform for a Hierarchical Foveal Machine Vision System · CVPR 1996
Parallel and multicore computing
task allocation		 0.011996
An MIMD Computing Platform for a Hierarchical Foveal Machine Vision System · CVPR 1996

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

static and dynamic resource allocation · 0.0MIMD parallel computing · 0.0
YearPublicationVenuePosition
1996 An MIMD Computing Platform for a Hierarchical Foveal Machine Vision System
abstract
A multiple instruction multiple data (MIMD) parallel computing platform built upon a network of TMS320C40/44s (C40/C44) for real-time image processing of a hierarchical foveal machine vision (HFMV) system is described in this paper. The architecture of the system, the parallel algorithm development environment, and strategies to map tasks into the computing platform are described. The platform supports both static and dynamic computing resource allocation. The performance of the computing platform is illustrated by examples.
Fenglei Du, Andrew Izatt, Cesar Bandera
 CVPR2