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VLDB 2026 Research / reviewers in the wild / expert

Lorenzo Vecci

dblp:61/4217 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 1998
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-author

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 graphics and multimedia
1 paper
Image and video processing · 50% Image and video coding · 50%
Theoretical computer science
1 paper
Algorithms and data structures · 100%

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

TopicWeightPapersLastEvidence papers
Image and video coding › shape coding
chain code		 0.011998
Fast Chain Coding of Region Boundaries · IEEE Trans. Pattern Anal. Mach. Intell. 1998
Image and video processing
image representation		 0.011998
Fast Chain Coding of Region Boundaries · IEEE Trans. Pattern Anal. Mach. Intell. 1998
Algorithms and data structures › signal processing algorithms
image processing algorithms		 0.011998
Fast Chain Coding of Region Boundaries · IEEE Trans. Pattern Anal. Mach. Intell. 1998
Algorithms and data structures › polynomial-time algorithms
linear-time algorithms		 0.011998
Fast Chain Coding of Region Boundaries · IEEE Trans. Pattern Anal. Mach. Intell. 1998

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

template-based conversion · 0.0single-pass algorithm · 0.0
YearPublicationVenuePosition
1998 Learning and Approximation Capabilities of Adaptive Spline Activation Function Neural Networks
Lorenzo Vecci, Francesco Piazza, Aurelio Uncini
 Neural Networks1
1998 Fast Chain Coding of Region Boundaries
abstract
A fast single-pass algorithm to convert a multivalued image from a raster-based representation into chain codes is presented. All chain codes are obtained in linear time with respect to the number of chain segments that are generated at each raster according to a set of templates. A formal statement and the complexity and performance analysis of the algorithm are given.
Primo Zingaretti, Massimiliano Gasparroni, Lorenzo Vecci
 IEEE Trans. Pattern Anal. Mach. Intell.3