Results 11 to 20 of about 482,653 (299)
Transfer Learning in Hierarchical Feature Spaces [PDF]
2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2015 Transfer learning provides an approach to solve target tasks more quickly and effectively by using previously acquired knowledge learned from source tasks. As one category of transfer learning approaches, feature-based transfer learning approaches aim to find a latent feature space shared between source and target domains.
Hua Zuo +4 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 +2 more
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Transfer Learning Oriented Text Feature Alignment Algorithm [PDF]
Jisuanji gongcheng, 2017 The inconsistency between source domain and target domain feature spaces results in accuracy decline of transfer learning.To resolve this problem,this paper proposes a different domain feature alignment method based on Word2Vec.Adjectives,adverbs,nouns ...
WEI Xiaocong,LIN Hongfei
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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 ...
George Retsinas +2 more
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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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Feature space transformation for transfer learning [PDF]
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012 In this paper, we propose a study on the use of weighted topological learning and matrix factorization methods to transform the representation space of a sparse dataset in order to increase the quality of learning, and adapt it to the case of transfer learning.
Nistor Grozavu +2 more
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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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Comparing Transfer Learning to Feature Optimization in Microstructure Classification
, 2021 Human analysis of research data is slow and inefficient. In recent years machine learning tools have advanced our capability to perform tasks normally carried out by humans, such as image segmentation and classification.
Taylor D., Sparks, Debanshu, Banerjee
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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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