Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 56,28
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Añadir al carritoCondición: New.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 58,22
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Chiron Media, Wallingford, Reino Unido
EUR 55,95
Cantidad disponible: 10 disponibles
Añadir al carritoPF. Condición: New.
Idioma: Inglés
Publicado por Springer Nature Switzerland, 2022
ISBN 10: 3031185757 ISBN 13: 9783031185755
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 58,84
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the Second MICCAI Workshop on Deep Generative Models, DG4MICCAI 2022, held in conjunction with MICCAI 2022, in September 2022. The workshops took place in Singapore.DG4MICCAI 2022 accepted 12 papers from the 15 submissions received. The workshop focusses on recent algorithmic developments, new results, andpromising future directions in Deep Generative Models. Deep generative modelssuch as Generative Adversarial Network (GAN) and Variational Auto-Encoder(VAE) are currently receiving widespread attention from not only the computervision and machine learning communities, but also in the MIC and CAI community.
Idioma: Inglés
Publicado por Springer International Publishing, 2022
ISBN 10: 3031185757 ISBN 13: 9783031185755
Librería: Buchpark, Trebbin, Alemania
EUR 39,66
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book constitutes the refereed proceedings of the Second MICCAI Workshop on Deep Generative Models, DG4MICCAI 2022, held in conjunction with MICCAI 2022, in September 2022. The workshops took place in Singapore. DG4MICCAI 2022 accepted 12 papers from the 15 submissions received. The workshop focusses on recent algorithmic developments, new results, and promising future directions in Deep Generative Models. Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community.