Visual Domain Adaptation in the Deep Learning Era

Discover the transformative power of transfer learning with "Visual Domain Adaptation in the Deep Learning Era" by Gabriela Csurka. Published by Springer International Publishing AG in 2022, this insightful paperback spans 168 pages and delves into the innovative techniques of domain adaptation (DA). As a vital component of modern machine learning, DA offers effective solutions for reducing the challenges of data annotation. This book explores how to leverage unlabeled data from target domains alongside labeled data or pre-trained models from related source domains. Perfect for researchers and practitioners in the field, Csurka's work provides a comprehensive overview of the latest advancements in deep learning, making it an essential addition to your library. Enhance your understanding of visual domain adaptation and its applications in today's data-driven world.