Explainable and Interpretable Models in Computer Vision and Machine Learning_Hugo Jair Escalante, Sergio Escalera.pdf

The Springer Series on Challenges in Machine Learning Hugo Jair Escalante · Sergio Escalera   Isabelle Guyon · Xavier Baró   Yağmur Güçlütürk · Umut Güçlü   Marcel van Gerven Editors Explainable and Interpretable Models in Computer Vision and Machine Learning The Springer Series on Challenges in Machine Learning Series editors Hugo Jair Escalante, INAOE, Puebla, Mexico Isabelle Guyon, INRIA, Université Paris Sud, Université Paris Saclay, Paris, France and ChaLearn, Berkeley, CA, USA Sergio Escalera, University of Barcelona, Barcelona, Spain The books of this innovative series collectpapers written by successful competitions in machine learning. They also include analyses of the challenges, tutorial material, dataset descriptions, and pointers to data and software. Together with the websites of the challenge competitions, they offer a complete teaching toolkit and a valuable resource for engineers and scientists. More information about this series athttp://www.springer.com/series/15602 Hugo Jair Escalante • Sergio Escalera Isabelle Guyon • Xavier Baró • Ya˘gmur Güçlütürk Umut Güçlü • Marcel van Gerven Editors ExplainableandInterpretable ModelsinComputerVision andMachineLearning 123 Editors Hugo Jair Escalante INAOE Puebla, Mexico Isabelle Guyon INRIA, Université Paris Sud, Université Paris Saclay, Paris, France ChaLearn Berkeley, CA, USA Ya˘gmur Güçlütürk Radboud University Nijmegen Nijmegen, The Netherlands Marcel van Gerven Radboud University Nijmegen Nijmegen, The Netherlands Sergio Escalera University of Barcelona Barcelona, Spain Xavier Baró Open University of Catalonia Barcelona, Spain Umut Güçlü Radboud University Nijmegen Nijmegen, The Netherlands ISSN 2520-131X ISSN 2520-1328 (electronic) The Springer Series on Challenges in Machine Learning ISBN 978-3-319-98130-7 ISBN 978-3-319-98131-4 (eBook) https://doi.org/10.1007/978-3-319-98131-4 Library of Congress Control Number: 2018962179 © Springer Nature Switzerland AG 2018 This work is subject to