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In this thesis, we explore Transductive Transfer Learning for visual recognition, where the data distributions of labeled source and unlabeled target domains ...
May 30, 2023 · PDF | On May 30, 2023, Jiaxing Huang published Transductive transfer learning for visual recognition | Find, read and cite all the research ...
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Jul 20, 2022 · I have reviewed the content and presentation style of this thesis and declare it is free of plagiarism and of sufficient grammatical clarity.
Transductive transfer learning is an effective way to adapt a network to a new target domain by utilizing a pretrained ATR network in the source ...
Missing: visual | Show results with:visual
Human action recognition is a hot topic in computer vision field. Various applicable approaches have been proposed to recognize different types of actions.
Missing: visual | Show results with:visual
Category models for objects or activities typically rely on supervised learning requiring sufficiently large training sets. Transferring knowledge from ...
Transfer learning (TL) is a machine learning (ML) technique where a model pre-trained on one task is fine-tuned for a new, related task.
Missing: visual | Show results with:visual
The concept of weight initialization technique for transfer learning refers to the practice of using pre-trained models that can be modified to solve new ...
Feb 12, 2024 · Transfer learning is a machine learning technique in which knowledge gained through one task or dataset is used to improve model performance ...
Missing: visual | Show results with:visual
May 23, 2023 · In this paper, we propose a CycleGAN-based transductive transfer learning approach with a CNN-based ATR classifier in the source and target ...