Explainable Deep Learning AI - Methods and Challenges (Paperback)

Explainable Deep Learning AI: Methods and Challenges presents the latest works of leading researchers in the XAI area, offering an overview of the XAI area, along with several novel technical methods and applications that address explainability challenges for deep learning AI systems. The book overviews XAI and then covers a number of specific technical works and approaches for deep learning, ranging from general XAI methods to specific XAI applications, and finally, with user-oriented evaluation approaches. It also explores the main categories of explainable AI - deep learning, which become the necessary condition in various applications of artificial intelligence. The groups of methods such as back-propagation and perturbation-based methods are explained, and the application to various kinds of data classification are presented.

General

Imprint:	Academic Press Inc
Country of origin:	United Kingdom
Release date:	2023
First published:	2023
Editors:	Jenny Benois-Pineau • Romain Bourqui • Dragutin Petkovic • Georges Quenot
Dimensions:	235 x 191mm (L x W)
Format:	Paperback
Pages:	395
ISBN-13:	978-0-323-96098-4
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems Promotions
LSN:	0-323-96098-7
Barcode:	9780323960984

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