Explainable Deep Learning/AI Call for Papers

Call for papers  ICPR2020 Workshop 

**************************Explainable Deep Learning/AI********************

The recent focus of AI and Pattern Recognition communities on the
supervised learning approaches, and particularly to Deep Learning /
AI, resulted in considerable increase of performance of Pattern
Recognition and AI systems, but also raised the question of the
trustfulness and explainability of their predictions for
decision-making.  Instead of developing and using Deep NNs as black
boxes and adapting known architectures to variety of problems, the
goal of explainable Deep Learning / AI is to propose methods to
“understand” and “explain” how the these systems produce
their decisions.  The goals of the workshop are to bring together
research community which is working on the question of improving
explainability of AI and Pattern Recognition algorithms and systems.
The topics of the workshop cover but are not limited to:

	"Sensing" or "salient features" of Neural Networks and AI
systems - explanation of which features for a given configuration
yield predictions both in spatial (images) and temporal (time-series,
video) data;

	Attention mechanisms in Deep Neural Networks and their

	For temporal data, the explanation of which features and at
    what time are the most prominent for the prediction and what are
    the time intervals when the contribution of each data is

	How the explanation can help on making Deep learning
	architectures more sparse (pruning) and light-weight;

	When using multimodal data how the prediction in data streams
    are correlated and explain each other;

	Automatic generation of explanations / justifications of
	algorithms and systems' decisions;

	Decisional uncertainly and explicability 

	Evaluation of the explanations generated by Deep Learning and
	other AI systems.

*** Pannel:  
Toward more explainable Deep Learning and AI systems”, Chair:
Dragutin Petcovic(SFSU,USA) Moderator will ask invited speakers to
briefly present their opinions and ideas on the topic of the panel and
then the audience will be invited to a discussion

*** Dates:

    Submission deadline : October 10th 2020
    Workshop author notification: November 10th 2020
    Camera-ready submission: November 15th 2020
    Finalized workshop program: December 1st 2020

*** Paper Submission:

The Proceedings of the EDL-AI 2020 workshop will be published in the
Springer Lecture Notes in Computer Science (LNCS) series. Papers will
be selected by a single blind (reviewers are anonymous) review
process. Submissions must be formatted in accordance with the
Springer's Computer Science Proceedings guidelines . Two types of
contribution will be considered:

    Full paper (12-15 pages)
    Short papers (6-8 pages)

*** Submission site: coming soon

Program Committee: 

Christophe Garcia (LIRIS, France) 
Hugues Talbot (EC, France) 
Dragutin Petkovic (SFSU,USA) 
Alexandre Benoît( LISTIC,France) 
Mark T. Keane (UCD, Ireland)
Georges Quenot(LIG, France) 
Stefanos Kolias (NTUA, Grece) 
Jenny Benois-Pineau(LABRI, France)
Hervé Le Borgne (LIST, France)
Noel O’Connor (DCU, Ireland)
Nicolas Thome(CNAM, France)

Jenny Benois-Pineau, Georges Quenot
Workshop Organizers

Jenny Benois-Pineau, 
Professeure en Informatique, 
Chargée de mission aux relations Internationales
Collège Sciences et Technologies, 
Université de Bordeaux