Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13003)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Included in the following conference series:
- DALI: MICCAI Workshop on Data Augmentation, Labelling, and Imperfections
- DGM4MICCAI: MICCAI Workshop on Deep Generative Models
Conference proceedings info: DALI 2021, DGM4MICCAI 2021.
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About this book
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 rigorousstudy of medical data related to machine learning systems.
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 rigorousstudy of medical data related to machine learning systems.
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Keywords
Table of contents (27 papers)
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Front Matter
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Image-to-Image Translation, Synthesis
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Front Matter
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Applications and Evaluation
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Front Matter
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AdaptOR Challenge
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Front Matter
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Other volumes
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Deep Generative Models, and Data Augmentation, Labelling, and Imperfections
Editors and Affiliations
Bibliographic Information
Book Title: Deep Generative Models, and Data Augmentation, Labelling, and Imperfections
Book Subtitle: First Workshop, DGM4MICCAI 2021, and First Workshop, DALI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings
Editors: Sandy Engelhardt, Ilkay Oksuz, Dajiang Zhu, Yixuan Yuan, Anirban Mukhopadhyay, Nicholas Heller, Sharon Xiaolei Huang, Hien Nguyen, Raphael Sznitman, … Yuan Xue
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-88210-5
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-88209-9Published: 30 September 2021
eBook ISBN: 978-3-030-88210-5Published: 29 September 2021
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XV, 278
Number of Illustrations: 22 b/w illustrations, 82 illustrations in colour
Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Artificial Intelligence, Computational Biology/Bioinformatics
