CFP
EDL-AI 2020: ICPR Workshop on Explainable Deep Learning-AI MiCo Milan Congress Center Milan, Italy, January 10-15, 2021 |
Conference website | https://edl-ai-icpr.labri.fr/ |
Submission link | https://easychair.org/conferences/?conf=edlai2020 |
Submission deadline | October 10, 2020 |
Call for papers ICPR’2020 Workshop **************************Explainable Deep Learning/AI******************** https://edl-ai-icpr.labri.fr/ Date: January 11th 2021 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 explanation; • 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 important; • 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 *** Important 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: will be open in September 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