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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.Produkteigenschaften
- Artikelnummer: 9783031206382
- Medium: Buch
- ISBN: 978-3-031-20638-2
- Verlag: Springer Nature Switzerland
- Erscheinungstermin: 01.05.2023
- Sprache(n): Englisch
- Auflage: 2023
- Produktform: Gebunden
- Gewicht: 981 g
- Seiten: 466
- Format (B x H x T): 160 x 241 x 30 mm
- Ausgabetyp: Kein, Unbekannt