Results 11 to 20 of about 2,076,683 (280)
Machines, 2022 Fault diagnosis of industrial bearings plays an invaluable role in the health monitoring of rotating machinery. In practice, there is far more normal data than faulty data, so the data usually exhibit a highly skewed class distribution.
Chuanzhu Hao, Junrong Du, Haoran Liang
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Person Re-identification Combined with Clothing Information Transfer
Jisuanji kexue yu tansuo, 2021 Person re-identification (Re-ID) is an identification method based on the overall characteristics of human body, which is usually used to judge whether there is a specific person in the image or video sequence.
YUAN Chunmiao, NIU Ying, GUO Tao, LI Xin
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Using Decoupled Features for Photorealistic Style Transfer
SIAM Journal on Imaging Sciences, 2023 In this work we propose a photorealistic style transfer method for image and video that is based on vision science principles and on a recent mathematical formulation for the deterministic decoupling of sample statistics. The novel aspects of our approach include matching decoupled moments of higher order than in common style transfer approaches, and ...
Trevor Canham +3 more
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Fuzzy Inference and Manifold Regularization Combined Feature Transfer Learning
Jisuanji kexue yu tansuo, 2020 Transfer learning leverages the rich data in the source domain to provide support for building accurate models in the target domain. Feature transfer learning is a kind of widely studied technology in transfer learning, but the existing feature transfer ...
SONG Yixuan, DENG Zhaohong, QIN Bin
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Transferable Deep Features for Keyword Spotting [PDF]
International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), 2018 Publication in the conference proceedings of IWCIM, Kos island, Greece ...
Retsinas, George +2 more
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Understanding How Feature Structure Transfers in Transfer Learning [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Transfer learning transfers knowledge across domains to improve the learning performance. Since feature structures generally represent the common knowledge across different domains, they can be transferred successfully even though the labeling functions across domains differ arbitrarily.
Tongliang Liu, Qiang Yang, Dacheng Tao
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IEEE Access, 2020 Machine learning methods have made great development in data-driven fault diagnosis of rolling bearings. But the intelligent fault diagnosis of intershaft bearing faces the following two dilemmas: 1) the fault vibration is extremely weak, and it is ...
Ya He +3 more
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Facial Expression Transfer Based on Conditional Generative Adversarial Networks
IEEE Access, 2023 With the development of computer vision and image transfer, facial expression transfer has been more and more widespread applications. But there are still some problems, such as lack of realistic expression, poor retention of facial identity features and
Yang Fan +3 more
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Knowledge Transfer Using Local Features [PDF]
2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning, 2007 We present a method for reducing the effort required to compute policies for tasks based on solutions to previously solved tasks. The key idea is to use a learned intermediate policy based on local features to create an initial policy for the new task. In order to further improve this initial policy, we developed a form of generalized policy iteration.
Martin Stolle, Christopher G. Atkeson
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Feature Spaces-based Transfer Learning [PDF]
Advances in Intelligent Systems Research, 2015 Transfer learning provides an approach to solve target tasks more quickly and effectively by using previouslyacquired knowledge learned from source tasks. Most of transfer learning approaches extract knowledge of source domain in the given feature space. The issue is that single perspective can‟t mine the relationship of source domain and target domain
Jie Lu +3 more
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