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)