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A. Rostampour

dblp:120/5889 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1982
—ORCID · none

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

Artificial intelligence and machine learning · 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 · 100%
Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing › parallel algorithms
parallel image processing
0.011982
Computational Cost of Image Registration with a Parallel Binary Array Processor · IEEE Trans. Pattern Anal. Mach. Intell. 1982
Image and video processing
image registration
0.011982
Computational Cost of Image Registration with a Parallel Binary Array Processor · IEEE Trans. Pattern Anal. Mach. Intell. 1982

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

global feature extraction · 0.0binary array processor · 0.0
YearPublicationVenuePosition
1982 Computational Cost of Image Registration with a Parallel Binary Array Processor
abstract
The application of a simulated binary array processor (BAP) to the rapid analysis of a sequence of images has been studied. Several algorithms have been developed which may be implemented on many existing parallel processing machines. The characteristic operations of a BAP are discussed and analyzed. A set of preprocessing algorithms are described which are designed to register two images of TV-type video data in real time. These algorithms illustrate the potential uses of a BAP and their cost is analyzed in detail. The results of applying these algorithms to FLIR data and to noisy optical data are given. An analysis of these algorithms illustrates the importance of an efficient global feature extraction hardware for image understanding applications.
Anthony P. Reeves, A. Rostampour
IEEE Trans. Pattern Anal. Mach. Intell.2