Domain Adaptation for Visual Understanding

Häftad, Engelska, 2021

Av Richa Singh, Mayank Vatsa, Vishal M. Patel, Nalini Ratha

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This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field.

Produktinformation

Utgivningsdatum2021-08-26
Mått155 x 235 x 9 mm
Vikt248 g
FormatHäftad
SpråkEngelska
Antal sidor144
FörlagSpringer Nature Switzerland AG
ISBN9783030306731

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Systemvetenskap och AI inom Data och it

Dr. Richa Singh is a Professor at Indraprastha Institute of Information Technology, Delhi, India. Dr. Mayank Vatsa is a Professor at the same institution. Dr. Vishal M. Patel is an Assistant Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University, Baltimore, MD, USA. Dr. Nalini Ratha is a Research Staff Member at the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA.

Domain Adaptation for Visual Understanding.- M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning.- XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings.- Improving Transferability of Deep Neural Networks.- Cross Modality Video Segment Retrieval with Ensemble Learning.- On Minimum Discrepancy Estimation for Deep Domain Adaptation.- Multi-Modal Conditional Feature Enhancement for Facial Action Unit Recognition.- Intuition Learning.- Alleviating Tracking Model Degradation Using Interpolation-Based Progressive Updating.