| Multi-layer collaborative optimization fusion for semi-supervised learning |
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| 作者姓名： | Quanbo GE Muhua LIU Jianchao ZHANG Jianqiang SONG Junlong ZHU Mingchuan ZHANG |
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| 作者单位： | 1. School of Automation, Nanjing University of Information Science and Technology;2. School of Information Engineering, Henan University of Science and Technology |
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| 基金项目： | supported in part by the National Natural Science Foundation of China (NSFC) (Nos. 62033010, 62102134)；;in part by the Aeronautical Science Foundation of China (No. 2019460T5001)；;in part by the Scientific and Technological Innovation Talents of Colleges and Universities in Henan Province, China (No. 22HASTIT014)； |
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| 摘 要： | Recently, the Cooperative Training Algorithm(CTA), a well-known Semi-Supervised Learning(SSL) technique, has garnered significant attention in the field of image classification.However, traditional CTA approaches face challenges such as high computational complexity and low classification accuracy. To overcome these limitations, we present a novel approach called Weighted fusion based Cooperative Training Algorithm(W-CTA), which leverages the cooperative training technique and unlabeled data to ...
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