Explainable and Interpretable Models in Computer Vision and Machine Learning

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Escalante, Hugo Jair (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Escalera, Sergio (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Guyon, Isabelle (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Baró, Xavier (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Güçlütürk, Yağmur (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Güçlü, Umut (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), van Gerven, Marcel (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: The Springer Series on Challenges in Machine Learning,
• Θέματα: 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...