Deep Generative Models, and Data Augmentation, Labelling, and Imperfections

Explore the cutting-edge realm of artificial intelligence with "Deep Generative Models, and Data Augmentation, Labelling, and Imperfections," authored by Sandy Engelhardt. This insightful book is the official 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), both held in October 2021. Published by Springer Nature Switzerland AG, this first edition spans 278 pages of rigorous research and innovative discussions that delve into the latest advancements in deep generative models and their applications in data augmentation and labelling challenges. Ideal for researchers, practitioners, and enthusiasts in the field of medical image computing, this book offers a comprehensive overview of the workshops' findings and is a valuable addition to any academic library. Don't miss out on this essential resource to enhance your understanding of these pivotal topics in AI and machine learning.