UID:
almahu_9949387859302882
Umfang:
X, 127 p. 44 illus., 36 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2022.
ISBN:
9783031185762
Serie:
Lecture Notes in Computer Science, 13609
Inhalt:
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.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031185755
Weitere Ausg.:
Printed edition: ISBN 9783031185779
Sprache:
Englisch
DOI:
10.1007/978-3-031-18576-2
URL:
https://doi.org/10.1007/978-3-031-18576-2