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Lev Zaidenberg

dblp:32/3516 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1987
—ORCID · none

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

Artificial intelligence and machine learning · 2Graphics, 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.

Artificial intelligence
2 papers
Knowledge representation and reasoning · 38% Planning, search and constraint satisfaction · 38% Image recognition and object detection · 25%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%
Theoretical computer science
1 paper
Computational geometry · 100%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
expert systems
0.011987
CAMEX - An Expert System for Process Planning on CNC Machines · AAAI 1987
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning
process planning
0.011987
CAMEX - An Expert System for Process Planning on CNC Machines · AAAI 1987
Computer vision › Image recognition and object detection
template matching
0.011984
Contextual Template Matching: A Distance Measure for Patterns with Hierarchically Dependent Features · IEEE Trans. Pattern Anal. Mach. Intell. 1984
Computational geometry
distance measures
0.011984
Contextual Template Matching: A Distance Measure for Patterns with Hierarchically Dependent Features · IEEE Trans. Pattern Anal. Mach. Intell. 1984

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

conditional pattern space · 0.0
YearPublicationVenuePosition
1987 CAMEX - An Expert System for Process Planning on CNC Machines
O. Eliyahu, Lev Zaidenberg, Moshe Ben-Bassat
AAAI2
1984 Contextual Template Matching: A Distance Measure for Patterns with Hierarchically Dependent Features
abstract
Contextual template matching refers to situations where the feature sets of the two templates under consideration may not be identical, but are rather contingent on the context within which these templates are observed. This paper addresses context-dependent template matching where the relevancy of certain features to a given object is contingent on the value of higher level features. In such situations portions of the patterns for two objects X and Y may not be comparable, and therefore classical distance measures are not applicable. A framework for describing pattern spaces with hierarchically dependent features-named conditional pattern spaces (CPS)-is presented, and a distance measure for comparing objects in a CPS is developed and illustrated on archaeological objects. This measure satisfies several desired properties of distance measures, such as the metric requirements.
Moshe Ben-Bassat, Lev Zaidenberg
IEEE Trans. Pattern Anal. Mach. Intell.2