Data Augmentation, Labelling, and Imperfections

Explore the innovative world of data science with Data Augmentation, Labelling, and Imperfections by Hien V. Nguyen. Published by Springer International Publishing AG in 2022, this insightful paperback offers a comprehensive look at the proceedings from the Second MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, held in Singapore. With a total of 124 pages, this first edition presents 12 carefully selected papers from 22 submissions, showcasing cutting-edge research and methodologies in the field. Perfect for researchers and practitioners alike, this book delves into the challenges and solutions surrounding data augmentation and labelling, making it an essential addition to your professional library. Enhance your understanding of data imperfections and their impact on machine learning and artificial intelligence. Don't miss the opportunity to gain valuable insights from leading experts in the field!