Explainable and Interpretable Models in Computer Vision and Machine Learning

• Corporate Author: SpringerLink (Online service)
• Other Authors: Escalante, Hugo Jair (Editor, http://id.loc.gov/vocabulary/relators/edt), Escalera, Sergio (Editor, http://id.loc.gov/vocabulary/relators/edt), Guyon, Isabelle (Editor, http://id.loc.gov/vocabulary/relators/edt), Baró, Xavier (Editor, http://id.loc.gov/vocabulary/relators/edt), Güçlütürk, Yağmur (Editor, http://id.loc.gov/vocabulary/relators/edt), Güçlü, Umut (Editor, http://id.loc.gov/vocabulary/relators/edt), van Gerven, Marcel (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: The Springer Series on Challenges in Machine Learning,
• Subjects: Artificial intelligence.; Optical data processing.; Pattern recognition.; Artificial Intelligence.; Image Processing and Computer Vision.; Pattern Recognition.

This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning. Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like per...