Interpretability in deep learning / Ayush Somani, Alexander Horsch, Dilip K. Prasad.

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Interpretability in deep learning / Ayush Somani, Alexander Horsch, Dilip K. Prasad.

9783031206399 (electronic bk.)
3031206398 (electronic bk.)
303120638X
9783031206382

Cham, Switzerland : Springer, 2023.

English

1 online resource (390 pages) : illustrations (black and white, and color).

10.1007/978-3-031-20639-9 doi

Q325.73

006.3/1

This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic. The book can be used as a monograph on interpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition.

Includes bibliographical references.

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Description based on print version record.

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