Scale Matters: Attribution Meets the Wavelet Domain to Explain Model Sensitivity to Image Corruptions

Neural networks have shown remarkable performance in computer vision, but their deployment in real-world scenarios is challenging due to their sensitivity to image corruptions. Existing attribution methods are uninformative for explaining the sensitivity to image corruptions, while the literature on robustness only provides model-based explanations. However, the ability to scrutinize models' behavior under image corruptions is crucial to increase the user's trust. Towards this end, we introduce the Wavelet sCale Attribution Method (WCAM), a generalization of attribution from the pixel domain to the space-scale domain. Attribution in the space-scale domain reveals where and on what scales the model focuses. We show that the WCAM explains models' failures under image corruptions, identifies sufficient information for prediction, and explains how zoom-in increases accuracy.Comment: main: 9 pages, appendix 19 pages, 32 figures, 5 table

EUCEET 2018: 4th International Conference on Civil Engineering Education: Challenges for the Third Millennium

World economy is changing rapidly. On the one hand, issues like health and safety, quality, resilience, sustainability, social justice and environment are increasing their weight for decision makers compared with traditional pecuniary considerations. On the other hand, the advent of cheap powerful computers, smart phones and robots is changing society drastically and also the economic interactions. The general agreed on professional requirements for future generations are the ability to interact with computers and robots, and the ability to do what these are not able to do (the so called soft skills as ethics or creativity). Civil Engineer practice is also impacted by this change. In the frame of Bologna Treaty, most universities are striving to adapt their educational contents as well as their training methods. Is Civil Engineering Education able to keep pace? In this book, this question is answered addressing the following topics: 1. New contents and capabilities: Resilience, sustainability, BIM (Building Information Modelling), soft skills, automation, artificial intelligence, smart cities, UAV (Unmanned Aerial Vehicles). 2. Methodology: Student centered teaching methods, online learning, flip learning, active learning, PBL (Project Based Learning) 3. The impact of educational policies: quality management, quality control and accreditation agencies, links between teaching, research and practicePostprint (published version