TY  - BOOK
AU  - Mukhopadhyay,Anirban
AU  - Oksuz,Ilkay
AU  - Engelhardt,Sandy
AU  - Zhu,Dajiang
AU  - Yuan,Yixuan
TI  - Deep Generative Models: Second MICCAI Workshop, DGM4MICCAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings 
T2  - Lecture Notes in Computer Science,
SN  - 9783031185762
U1  - 006.37 23
PY  - 2022///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Computer vision
KW  - Machine learning
KW  - Education-Data processing
KW  - Application software
KW  - Computer Vision
KW  - Machine Learning
KW  - Computers and Education
KW  - Computer and Information Systems Applications
N2  - 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
UR  - https://doi.org/10.1007/978-3-031-18576-2
ER  -