Deep generative models: Second MICCAI Workshop, DGM4MICCAI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings
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 foc...
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| Corporate Authors: | , |
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| Other Authors: | , , , , |
| Format: | Conference Paper |
| Language: | English |
| Published: |
Cham
Springer Nature Switzerland
2022.
Cham Imprint: Springer 2022. |
| Edition: | 1st ed. 2022. |
| Series: | Lecture Notes in Computer Science
13609 |
| DOI: | 10.1007/978-3-031-18576-2 |
| Subjects: | |
| Online Access: | Resolving-System, lizenzpflichtig: https://doi.org/10.1007/978-3-031-18576-2
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| Author Notes: | Anirban Mukhopadhyay, Ilkay Oksuz, Sandy Engelhardt, Dajiang Zhu, Yixuan Yuan (eds.) |
| Summary: | 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. |
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| Physical Description: | Online Resource |
| ISBN: | 9783031185762 |
| DOI: | 10.1007/978-3-031-18576-2 |