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Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues
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Deep Generative Models, and Data Augmentation, Labelling, and Imperfections - First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings (Paperback, 1st ed. 2021)
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Deep Generative Models, and Data Augmentation, Labelling, and Imperfections - First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings (Paperback, 1st ed. 2021)
Series: Image Processing, Computer Vision, Pattern Recognition, and Graphics, 13003
Expected to ship within 10 - 15 working days
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This book constitutes the refereed proceedings of the First MICCAI
Workshop on Deep Generative Models, DG4MICCAI 2021, and the First
MICCAI Workshop on Data Augmentation, Labelling, and Imperfections,
DALI 2021, held in conjunction with MICCAI 2021, in October 2021.
The workshops were planned to take place in Strasbourg, France, but
were held virtually due to the COVID-19 pandemic. DG4MICCAI 2021
accepted 12 papers from the 17 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. For DALI 2021,
15 papers from 32 submissions were accepted for publication. They
focus on rigorous study of medical data related to machine learning
systems.
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