Connectionists: CfP for SS on Graphs for Pattern Recognition: Representations, Theory and Applications at the 3rd ICPRAI in Paris, France
Donatello Conte
donatello.conte at univ-tours.fr
Sun Nov 28 16:25:24 EST 2021
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Apologies for multiples copies
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Call for Papers
Graphs for Pattern Recognition: Representations, Theory and Applications
Special Session at
the 3rd International Conference on Pattern Recognition and Artificial Intelligence
June 1- 3, 2022
https://icprai2022.sciencesconf.org/
Important Dates
Paper submission deadline: December 15th, 2021
Author notification: March 8th, 2022
Camera ready deadline: March 22th, 2022
Early bird registration deadline: April 1st, 2022
Time of the conference: June 1st to 3rd, 2022
Scientific Program Committee
Isabelle Bloch (FR)
Luc Brun (FR)
Vincenzo Carletti (IT)
Donatello Conte (FR)
H. Edelsbrunner (A)
Benoit Gaüzere (FR)
Rocio Gonzalez-Diaz (Spain)
Marco Gori (IT)
Yll Haxhimusa (A)
Walter G. Kropatsch (A)
Xiaoyi Jiang (G)
J.Y. Ramel (FR)
Luca Rossi (UK)
Francesc Serratosa (Spain)
Ali Shokoufandeh (US)
Mario Vento (IT)
Pasquale Foggia (IT)
Motivations and topics
Graphs have gained a lot of attention in the pattern recognition community thanks to their ability to encode both topological,
geometrical, and semantic information. Despite their invaluable descriptive power and their invariance to diverse geometric deformations,
their arbitrarily complex structured nature poses serious challenges when they are involved in Pattern Recognition and Artificial Intelligence.
Some challenging Problems are: a non-unique representation of data, heterogeneous attributes (symbolic, numeric, etc.), highly complex algorithms like (sub-)graph matching.
This Special Session intends to focus on all aspects of graph-based representations in Pattern Recognition and Artificial Intelligence, from theoretical to applications concerns.
It spans, but is not limited to, the following topics:
● Dynamic, spatial and temporal graphs
● Graph representations and methods in computer vision
● Geometry and Topology in Graphs
● Graph Neural Networks
● Benchmarks for Graphs in Pattern Recognition
● Graph Learning and Classification
● Graph Matching
● Social Networks Analysis
● Graph Representation Learning
Track Chairs
Walter G. Kropatsch (TU Wien)
Donatello Conte (University of Tours)
Vincenzo Carletti (University of Salerno)
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