Deep Generative Models / Lecture Notes in Computer Science Bd.13609 (PDF)
Second MICCAI Workshop, DGM4MICCAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
(Sprache: Englisch)
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...
DG4MICCAI 2022 accepted 12 papers from...
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Produktinformationen zu „Deep Generative Models / Lecture Notes in Computer Science Bd.13609 (PDF)“
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.
Bibliographische Angaben
- 2022, 1st ed. 2022, 127 Seiten, Englisch
- Herausgegeben: Anirban Mukhopadhyay, Ilkay Oksuz, Sandy Engelhardt, Dajiang Zhu, Yixuan Yuan
- Verlag: Springer Nature Switzerland
- ISBN-10: 3031185765
- ISBN-13: 9783031185762
- Erscheinungsdatum: 07.10.2022
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Größe: 22 MB
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