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Beschreibung
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.
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 01. Mai 2023 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 981 Gramm |
| Format | Hardcover |
| ISBN-13 | 9783031206382 |
| Seiten | 466 |