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个人简介

叶敏超,中国计量大学信息工程学院计算机科学与技术学科副教授。近年来主要研究高光谱图像的跨场景特征提取、特征选择、分类算法,以及图非负矩阵分解在高光谱图像中的应用。目前在研国家自然科学基金青年项目:基于特征子空间学习的跨场景异构高光谱图像分类。在高光谱图像处理方向的国际会议IEEEIGARSS、国际期刊IEEETransactionsonGeoscienceandRemoteSensing、IEEEJournalofSelectedTopicsinAppliedEarthObservations,以及机器学习方向期刊NeuralComputingandApplications上发表有学术论文。 教育、工作经历: 2006.9-2010.6四川大学计算机学院计算机科学与技术本科 2010.9-2016.3浙江大学计算机学院计算机科学与技术博士(直接攻博) 2016.6-至今中国计量大学信息工程学院计算机科学与技术教师

研究领域

高光谱图像处理机器学习模式识别

近期论文

查看导师新发文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

1. Minchao Ye, Chenxi Ji, Hong Chen, et al. Residual deep PCA-based feature extraction for hyperspectral image classification[J]. Neural Computing and Applications, 2019. 2. Minchao Ye, Hong Chen, Chenxi Ji, et al. Spectral-Spatial Joint Noise Estimation for Hyperspectral Images[C]//IEEE International Geoscience and Remote Sensing Symposium. 2019: 230-233 3. Minchao Ye, Chenxi Ji, Hong Chen, et al. Feature selection for cross-scene hyperspectral image classification using cross-domain ReliefF[J]. International Journal of Wavelets, Multiresolution and Information Processing, 2019: 1950039. 4. Hong Chen, Minchao Ye, Huijuan Lu, et al. Dual Dictionary Learning for Mining a Unified Feature Subspace between Different Hyperspectral Image Scenes[C]//IEEE International Geoscience and Remote Sensing Symposium. 2019: 1096-1099. 5. Chenxi Ji, Minchao Ye, Huijuan Lu, et al. Feature Extraction of Hyperspectral Imagery Based on Deep NMF[C]//IEEE International Geoscience and Remote Sensing Symposium. 2019: 1092-1095. 6. Minchao Ye, Yongqiu Xu, Huijuan Lu, et al. Cross-Scene Feature Selection for Hyperspectral Images Based on Cross-Domain Information Gain[C]//IEEE International Geoscience and Remote Sensing Symposium. 2018: 4764-4767. 7. Minchao Ye, Yuntao Qian, Jun Zhou, et al. Dictionary Learning-Based Feature-Level Domain Adaptation for Cross-Scene Hyperspectral Image Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(3):1544-1562. 8. Minchao Ye, Wenbin Zheng, Huijuan Lu, et al. Cross-scene hyperspectral image classification based on DWT and manifold-constrained subspace learning[J]. International Journal of Wavelets, Multiresolution and Information Processing, 2017, 15(06): 1750062. 9. Minchao Ye, Yuntao Qian, Jun Zhou. Multitask sparse nonnegative matrix factorization for joint spectral-spatial hyperspectral imagery denoising[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(5): 2621-2639.

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