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Interpretability in Deep Learning

Interpretability in Deep Learning

Alexander Horsch / Ayush Somani / Dilip K. Prasad

46,91 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2023
Materia
Inteligencia artificial
ISBN:
9783031206405
46,91 €
IVA incluido
Disponible

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Sobre IBD

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.    

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