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湖南大学 [9]

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	Retrieving Water Quality Parameters from Noisy-Label Data Based on Instance Selection 期刊论文 REMOTE SENSING, 2022, 卷号: 14, 期号: 19 作者: Liu, Yuyang; Liu, Jiacheng; Zhao, Yubo; Wang, Xueji; Song, Shuyao 收藏 \| 浏览/下载：19/0 \| 提交时间：2022/10/28 turbidity noisy-label learning hyperspectral image water quality parameter UAV
	Narrowing the Gap: Improved Detector Training With Noisy Location Annotations 期刊论文 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6369-6380 作者: Wang, Shaoru; Gao, Jin; Li, Bing; Hu, Weiming 收藏 \| 浏览/下载：11/0 \| 提交时间：2022/11/14 Annotations Noise measurement Detectors Task analysis Training Object detection Degradation Object detection noisy label Bayesian estimation teacher-student learning
	Semi-supervised anomaly detection in dynamic communication networks 期刊论文 INFORMATION SCIENCES, 2021, 卷号: 571, 页码: 527-542 作者: Meng, Xuying; Wang, Suhang; Liang, Zhimin; Yao, Di; Zhou, Jihua 收藏 \| 浏览/下载：49/0 \| 提交时间：2021/12/01 Anomaly detection Semi-supervised learning Generative adversarial networks Self-learning
	Improving Distant Supervised Relation Extraction with Noise Detection Strategy 期刊论文 APPLIED SCIENCES-BASEL, 2021, 卷号: 11, 期号: 5, 页码: 1-14 作者: Meng, XY (Meng, Xiaoyan)[ 1,2,3,4 ]; Jiang, TH (Jiang, Tonghai)[ 1,3 ]; Zhou, X (Zhou, Xi)[ 1,2,3 ]; Ma, B (Ma, Bo)[ 1,2,3 ]; Wang, Y (Wang, Yi)[ 1,2,3 ] 收藏 \| 浏览/下载：37/0 \| 提交时间：2021/05/06 relation extraction distant supervision noise detection
	Density Peak-Based Noisy Label Detection for Hyperspectral Image Classification. 期刊论文 IEEE Transactions on Geoscience & Remote Sensing, 2019, 卷号: Vol.57 No.3, 页码: 1573-1584 作者: Tu, Bing; Zhang, Xiaofei; Kang, Xudong; Zhang, Guoyun; Li, Shutao 收藏 \| 浏览/下载：16/0 \| 提交时间：2019/12/13 Clustering algorithms Density peak (DP) clustering hyperspectral image (HSI) Hyperspectral imaging Labeling Noise measurement noisy label detection Support vector machines support vector machines (SVMs) Training
	Density Peak-Based Noisy Label Detection for Hyperspectral Image Classification 期刊论文 IEEE Transactions on Geoscience and Remote Sensing, 2019, 卷号: Vol.57 No.3, 页码: 1573-1584 作者: Bing Tu; Xiaofei Zhang; Xudong Kang; Guoyun Zhang; Shutao Li 收藏 \| 浏览/下载：11/0 \| 提交时间：2019/12/13 Noise measurement Training Clustering algorithms Hyperspectral imaging Labeling Support vector machines Density peak (DP) clustering hyperspectral image (HSI) noisy label detection support vector machines (SVMs)
	Spatial Density Peak Clustering for Hyperspectral Image Classification With Noisy Labels 期刊论文 IEEE Transactions on Geoscience and Remote Sensing, 2019, 卷号: Vol.57 No.7, 页码: 5085-5097 作者: Bing Tu; Xiaofei Zhang; Xudong Kang; Jinping Wang; Jón Atli Benediktsson 收藏 \| 浏览/下载：6/0 \| 提交时间：2019/12/13 Noise measurement Training Correlation Clustering algorithms Hyperspectral imaging Labeling Density peak (DP) clustering hyperspectral image (HSI) noisy label detection support vector machines (SVMs)
	Density Peak-Based Noisy Label Detection for Hyperspectral Image Classification. 期刊论文 IEEE Transactions on Geoscience & Remote Sensing, 2019, 卷号: Vol.57 No.3, 页码: 1573-1584 作者: Tu, Bing; Zhang, Xiaofei; Kang, Xudong; Zhang, Guoyun; Li, Shutao 收藏 \| 浏览/下载：4/0 \| 提交时间：2019/12/13 Clustering algorithms Density peak (DP) clustering hyperspectral image (HSI) Hyperspectral imaging Labeling Noise measurement noisy label detection Support vector machines support vector machines (SVMs) Training
	Density Peak-Based Noisy Label Detection for Hyperspectral Image Classification 期刊论文 IEEE Transactions on Geoscience and Remote Sensing, 2019, 卷号: Vol.57 No.3, 页码: 1573-1584 作者: Tu, Bing; Zhang, Xiaofei; Kang, Xudong; Zhang, Guoyun; Li, Shutao 收藏 \| 浏览/下载：2/0 \| 提交时间：2019/12/13
	Density Peak-Based Noisy Label Detection for Hyperspectral Image Classification. 期刊论文 IEEE Transactions on Geoscience & Remote Sensing, 2019, 卷号: Vol.57 No.3, 页码: 1573-1584 作者: Tu, Bing; Zhang, Xiaofei; Kang, Xudong; Zhang, Guoyun; Li, Shutao 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/12/17 Clustering algorithms Density peak (DP) clustering hyperspectral image (HSI) Hyperspectral imaging Labeling Noise measurement noisy label detection Support vector machines support vector machines (SVMs) Training

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