深度学习、计算机视觉、数据挖掘

《机器学习》、《数据挖掘》、《模式识别》

[1] 山东省自然科学基金项目（No：ZR2022MF260），“基于生成对抗网络的图像生成学习方法研究”，2023.01-2025.12, 主持；

[2] 国家自然科学基金项目（No：62272375），“面向真实场景的遥感图像全色锐化深度学习方法研究”，2023.01-2026.12, 排名第2；

[3] 国家重点研发计划项目（No：2021YFA1000102），“油气管网安全运维的大数据分析理论、算法及应用”，2022.01-2025.12, 参与；

[4] 国家自然科学基金项目（No：61976245），“面向复杂数据的多粒度知识发现建模与三支决策分析”，2020.01-2023.12, 排名第2；

[5] 国家自然科学基金项目（No：61673396），“多尺度概念格的构造与知识发现方法研究”，2017.01-2020.12, 主持；

[6] 中国石油大学（华东）自主创新项目，“基于粗糙集理论的复杂信息系统信息分析方法”, 2015.01-2017.12, 主持；

[7] 国家自然科学基金项目（No：61363056），“优势关系下的区间值信息系统知识获取方法”， 2014.01-2017.12，主持；

[8] 国家社会科学基金项目（No：14XXW004），“非常规突发事件舆情信息检测与分析方法研究”，2014.01-2016.12，排名第2；

[9] 国家自然科学基金项目（No：61173181），“基于粗糙集与概念格相韵合的数据分析理论与方法研究”，2012.01-2015.12，主持；

[10] 教育部一般科技项目（No：11XJJAZH001），“生产过程智能调度方法研究及调度系统设计”，2012.01-2015.12，排名第2；

[11] 国家自然科学基金项目（No：60963006），“模糊与集值形式背景下的形式概念分析理论与知识获取”，2010.01-2012.12，主持；

[12] 教育部科技项目（No：09YJCZH082），“基于粗糙集理论和形式概念分析的知识发现方法融合研究”，2010.01-2012.12，主持；

[13] 省自然科学基金项目（No：2007GQS0074），“概念性数据的属性约简与规则获取”，2008.01-2009.12，主持。

[14] 国家自然科学基金项目（No：60763001）：“基于隐式反馈和伪反馈的XML文本文档检索技术研究”，2008.01-2010.12，排名第2。

[1] Shao Mingwen, Zhiyong Hu, Wu Weizhi, Liu Huan, Graph Neural Networks Induced by Concept Lattices for Classification, International Journal of Approximate Reasoning, 已录用. (SCI 2区)

[2] Shao Mingwen, QiaoYuanjian, Meng Deyu, Zuo Wangmeng, Uncertainty-Guided Hierarchical Frequency Domain Transformer for Image, Knowledge-Based Systems, 已录用. (SCI 1区 )

[3] Yang Jianxin, Shao Mingwen*, Liu Huan, Zhuang Xinkai, Generating Adversarial Samples by Manipulating Image Features with Auto-encoder, International Journal of Machine Learning and Cybernetics, 已录用. (SCI 3区)

[4] Wang Changzhong, Lv Xiang, Shao Mingwen, Qian Yuhua, Zhang Yang, A novel fuzzy hierarchical fusion attention convolution neural network for medical image super-resolution reconstruction, Information Sciences, 2023, 622: 424-436. (SCI 1区 )

[5] Zhuang Xinkai, Shao Mingwen*, Gao Wei, and Yang Jianxin. An adaptive fine-tuning strategy for few-shot learning, Journal of Electronic Imaging, 2022, http://dx.doi.org/10.1117/1.JEI.31.6.063010. (SCI 4区 )

[6] Liu Zeting, Shao Mingwen*, Sun Yuantao, Peng Zilu, Multi-task feature-aligned head in one-stage object detection, Signal, Image and Video Processing, 2022, https://doi.org/10.1007/s11760-022-02342-9. (SCI 4区 )

[7] Liu Baichen, Han Zhi, Chen Xi’ai, Shao Mingwen, Jia Huidi, Wang Yanmei, Tang Yandong, A novel compact design of convolutional layers with spatial transformation towards lower-rank representation for image classification, Knowledge-Based Systems, 2022, 255: 109723. (SCI 1区 )

[8] Shao Mingwen*, Wang Chao, Meng Deyu, Zuo Wangmeng, Efficient Pyramidal GAN for Versatile Missing Data Reconstruction in Remote Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5626014. (SCI 2区 )

[9] Shao Mingwen*, Zhang Wei, Li Yunhao, Fan Bingbing, Branch Aware Assignment for Object Detection, 2022, The Visual Computer, 2022，https://doi.org/10.1007/ s00371-022-02691-z. (SCI 3区 )

[10] Peng Zilu, Shao Mingwen*, Sun Yuantao, Li Cunhe, IDLA: Instance-based Dynamic Label Assignment for Object Detection, Journal of Electronic Imaging, 2022, 31(4): 043009. (SCI 4区)

[11] Liu Huan, Shao Mingwen*, Wang Chao, Cao Feilong, Image Super-Resolution Using a Simple Transformer without Pre-training, Neural Processing Letters, 2022, https://doi.org/10.1007/s11063-022-10948-w. (SCI 3区)

[12] Wan Yecong, Cheng Yuanshuo, Shao Mingwen*, Gonzàlezb Jordi, Image Rain Removal and Illumination Enhancement Done in One Go, Knowledge-Based Systems, 2022, 252: 109244. (SCI 1区)

[13] Wang Chao, Shao Mingwen*, Meng Deyu, Zuo Wangmeng, Dual-Pyramidal Image Inpainting with Dynamic Normalization, IEEE Transactions on Circuits and Systems for Video Technology, 2022, 32(9): 5975. (SCI 1区)

[14] Wan Yecong, Cheng Yuanshuo, Shao Mingwen*, MSLANet: Multi-scale Long Attention Network for Skin Lesion Classication, Applied Intelligence, 2022, https://doi.org/10.1007/s10489-022-03320-x. (SCI 2区)

[15] Fan Bingbing, Shao Mingwen*, Li Yunhao, Li Cunhe, Global Contextual Attention for Pure Regression Object Detection, International Journal of Machine Learning and Cybernetics, 2022, 13: 2189–2197. (SCI 2区)

[16] Kuang Jiandong Shao Mingwen*, Wang Ran, Zuo Wangmeng, Ding Weiping, Network Pruning via Probing the Importance of Filters, International Journal of Machine Learning and Cybernetics, 2022, 13: 2403–2414. (SCI 2区)

[17] Shao Mingwen, Zhang Wei*, Li Yunhao, Fan Bingbing, Enhanced Feature Pyramidal Network for Object Detection, Journal of Electronic Imaging, 2022, 31(1): 013030. (SCI 4区)

[18] Guo Chen, Lin Yaojin, Chen Shengyu, Zeng Zhichun, Shao Mingwen, Li Shaozi, From the whole to detail: Progressively sampling discriminative parts for fine-grained recognition, Knowledge-Based Systems, 2022, 235: 107651. (SCI 1区)

[19] Shao Mingwen*, Liu Shuqi, Wang Ran, Zhang Gaozhi, An Adversarial sample defense method based on multi-scale GAN, International Journal of Machine Learning and Cybernetics, 2021, 12:3437–3447. (SCI 2区)

[20] Shao Mingwen, Zhang Youcai*, Liu Huan, Wang Chao, Li Le, Shao Xun, DMDIT: Diverse Multi-Domain Image-to-Image Translation, Knowledge-Based Systems, 2021, 229(2):107311. (SCI 1区)

[21] Shao Mingwen*, Dai Junhui, Wang Ran, Zuo Wangmeng, CSHE: Network Pruning by using Cluster Similarity and Matrix Eigenvalues, International Journal of Machine Learning and Cybernetics, 2022, 13: 371–382. (SCI 2区)

[22] Gao Wei, Shao Mingwen*, Shu Jun, Zhuang Xinkai, Meta-BN Net for Few-Shot Learning, Frontiers of Computer Science, 2023, 17: 171302. (SCI 2区)

[23] Li Yunhao, Shao Mingwen*, Fan Bingbing, Zhang Wei, Multi-scale Global Context Feature Pyramid Network for Object Detector, Signal, Image and Video Processing, 2022, 16: 705-713. (SCI 3区)

[24] Wang Chao, Shao Mingwen*, Zhang Wentao, and Zhang Youcai, A Context-Based Multi-Scale Discriminant Model for Natural Image Inpainting, AATCC Journal of Research, 2021, 1:1-14. DOI: 10.14504/ajr.8.S1.1. (SCI 4区)

[25] Shao Mingwen*, Li Le*, Meng Deyu, Zuo Wangmeng, Uncertainty Guided Multi-scale Attention Network for Raindrop Removal from A Single Image, IEEE Transactions on Image Processing, 2021, 30: 4828-4839. (SCI 1区)

[26] Shao Mingwen*, Zhang Youcai, Fan Yuan, Zuo Wangmeng, Meng Deyu, IIT-GAT: Instance-level Image Transformation via Unsupervised Generative Attention Networks with Disentangled Representations, Knowledge-Based Systems, 2021, 225, 107122. (SCI 1区)

[27] Hu Zhiyong, Shao Mingwen*, Liu Huan, Mi Jusheng, Cognitive Computing and Rule Extraction in Generalized One-sided Formal Contexts, Cognitive Computing,2021, DOI: 10.1007/s12559-021-09868-z. (SCI 2区). (SCI 2区)

[28] Shao Mingwen*, Zhang Gaozhi, Zuo Wangmeng, Meng Deyu, Target Attack on Biomedical Image Segmentation Model based on Multi-scale Gradients, Information Sciences, 2021, 554: 33–46. (SCI 1区)

[29] Wang Chao, Shen Haozhen, Fan Fan, Shao Mingwen, Yang Chuansheng, Luo, Jiancheng, EAA-Net: A novel edge assisted attention network for single image dehazing, Knowledge-Based Systems, 2021, 228, 107279. (SCI 1区)

[30] Shao Mingwen*, Chao Wang, Wu Tianjun, Meng Deyu, Luo Jiancheng, Context-based Multi-scale Unified Network for Missing Data Reconstruction in Remote Sensing images, IEEE Geoscience and Remote Sensing Letters, 2022, 19: 8001205. (SCI 2区)

[31] 张高志，刘新平，邵明文*，基于GAN 的对抗样本生成与白盒目标攻击，模式识别与人工智能，2020，33(9): 1-9. (EI 收录)

[32] Shao Mingwen*, Li Le, Wang Hong, Meng Deyu, Selective Generative Adversarial Network for Raindrop Removal from A Single Image, Neurocomputing, 2021, 426: 265-273. (SCI 2区)

[33] Shao Mingwen*, Dai Junhui, Kuang Jiandong, Meng Deyu, A dynamic CNN pruning method based on matrix similarity, 2020, Signal, Image and Video Processing, 2021, 15:381–389. (SCI 4区)

[34] Liu Shuqi, Shao Mingwen*, Liu Xinping, GAN-based Classifier Protection against adversarial attacks, Journal of Intelligent & Fuzzy Systems, 2020, 39(5): ‏ 7085-7095. (SCI 4区)

[35] Wang Changzhong, Wang Yan, Shao Mingwen, Qian Yuhua, Chen Degang, Fuzzy rough attribute reduction for categorical data, IEEE Transactions on Fuzzy Systems, 2020, 28(5): 818-829. (SCI 1区，SCI高被引论文)

[36] Shao Mingwen*, Zhang Wentao, Zuo Wangmeng, Meng Deyu, Multi-scale generative adversarial inpainting network based on cross-layer attention transfer mechanism, Knowledge-Based Systems, 2020,196: 105778. (SCI 2区)

[37] Song Xiaoxia, Shao Mingwen*, Zuo Wangmeng, Li Cunhe, Face attribute editing based on generative adversarial networks, Signal, Image and Video Processing, 2020, 14: 1217–1225. (SCI 4区)

[38] Fan Yuan, Shao Mingwen*, Zuo Wangmeng, Li Qingyun, Unsupervised image‑to‑image translation using intra‑domain reconstruction loss, International Journal of Machine Learning and Cybernetics, 2020, 11: 2077–2088. (SCI 3区)

[39] Wang Changzhong, Huang Yang, Shao Mingwen, Hu, Qinghua, Chen Degang, Feature Selection Based on Neighborhood Self-Information, IEEE Transactions on Cybernetics, 2020, 50(9): 4031-4042. (SCI 1区，SCI高被引论文)

[40] Shao Mingwen*, Lv mengmeng, Li kewen, Wang Changzhong, The Construction of Attribute (Object)-oriented Multi-granularity Concept Lattices，International Journal of Machine Learning and Cybernetics, 2020, 11: 1017–1032. (SCI 3区 )

[41] Shao Mingwen*, Wu Weizhi, Wang Xi-Zhao, Wang Changzhong, Knowledge reduction methods of covering approximate spaces based on concept lattice, Knowledge-Based Systems，2020, 191(5):1-9. (SCI 2区)

[42] Wei Yiwei, Wang Leiquan, Cao Haiwen, Shao Mingwen, Wu Chunlei*, Multi-Attention Generative Adversarial Network for image captionin， Neurocomputing, 2020, 387: 91–99. (SCI 2区)

[43] Wang Changzhong, Huang Yang, Fan Xiaodong, Shao Mingwen, Homomorphism between ordered decision systems, Soft Computing, 2019, 23: 365-374. (SCI 3区)

[44] Wang Changzhong, Shi Yunpeng, Fan Xiaodong, Shao Ming-Wen, Attribute reduction based on k-nearest neighborhood rough sets, International Journal of Approximate Reasoning, 2019, 106:18-31. (SCI 3区).

[45] Wang Changzhong, Huang Yang, Shao Mingwen, Fan Xiaodong, Fuzzy rough set-based attribute reduction using distance measures, Knowledge-Based Systems, 2019, 164: 205-212. (SCI 2区，SCI高被引论文).

[46] Wang Changzhong, Huang Yang, Shao Mingwen, Chen Degang, Uncertainty measures for general fuzzy relations, Fuzzy Sets and System, 2019, 360(1): 82-96. (SCI 1区).

[47] Shao Mingwen*, Wu Weizhi, Wang Changzhong, Axiomatic characterizations of adjoint generalized (dual) concept systems, Journal of Intelligent & Fuzzy Systems, 2019，37: 3629-3638. (SCI 4区)

[48] Wu Weizhi, Shao Mingwen, Wang Xia, Using single axioms to characterize (S, T)‑intuitionistic fuzzy rough approximation operators, International Journal of Machine Learning and Cybernetics, 2019,10:27-42. (SCI 3区)

[49] Shao Mingwen, Guo Li, Wang Changzhong, Connections between two- universe rough sets and formal concepts, International Journal of Machine Learning and Cybernetics, 2018, 9(11): 1869-1877. (SCI 3区)

[50] Wang Changzhong, He Qiang, Shao Mingwen, Hu Qinghua, Feature selection based on maximal neighborhood discernibility, International Journal of Machine Learning and Cybernetics, 2018, 9:1929-1940. (SCI 3区).

[51] Wang Changzhong, He Qiang, Shao Mingwen, Xu Yangyang, Hu Qinghua, A unified information measure for general binary relations, Knowledge-Based Systems, 2017, 135: 18-28. (SCI 2区)

[52] Gong Faming, Shao Mingwen*, Qiu Guofang, Concept Granular Computing Systems and Their Approximation Operators, International Journal of Machine Learning and Cybernetics, 2017, 8(2): 627–640. (SCI 3区)

[53] Li Kewen, Shao Mingwen*, Wu Weizhi, A data reduction method in formal fuzzy contexts, International Journal of Machine Learning and Cybernetics, 8(4) (2017) 1145–1155. (SCI 3区)

[54] Shao Mingwen*, Li Kewen, Attribute reduction in generalized one-sided formal contexts, Information Sciences, 2017, 378(1): 317-327. (SCI 1区)

[55] Wang Changzhong, Shao Mingwen, He Qiang, Qian Yuhua, Qi Yali, Feature subset selection based on fuzzy neighborhood rough sets, Knowledge-Based Systems, 2016, 111: 173–179. (SCI 1区)

[56] Wang Changzhong, Qi Yali, Shao Mingwen, Hu Qinghua, Chen Degang, Qian Yuhua, Lin Yaojin, A Fitting Model for Feature Selection with Fuzzy Rough Sets, IEEE Transactions On Fuzzy Systems, 2017, 25(4):741-753. (SCI 1区，SCI高被引论文)

[57] Xin Li, Shao Mingwen*, Xing-Min Zhao, Constructing lattice based on irreducible concepts, International Journal of Machine Learning and Cybernetics, 2017, 8(1): 109-122. (SCI 3区)

[58] Shao Mingwen*, Leung Yee, Wang Xizhao, Wu Weizhi, Granular Reducts of Formal Fuzzy Contexts, Knowledge-Based Systems, 2016, 114(15): 156-166. (SCI 1区)

[59] Wu Weizhi, Xu Youhong, Shao Mingwen, Wang Guoyin, Axiomatic characterizations of (S,T)-fuzzy rough approximation operators, Information Sciences, 2016, 334-335: 17–43. ( SCI 2区)

[60] Wang Changzhong, Shao Mingwen*, Sun Baiqing, Hu Qinghua. An improved attribute reduction scheme with covering based rough sets, Applied Soft Computing, 2015, 26: 235-243. ( SCI 2区)

[61] Shao Mingwen*, Yang Hongzhi, Wu Weizhi. Knowledge Reduction in Formal Fuzzy Contexts, Knowledge-Based Systems, 2015,73: 265-275. ( SCI 1区)

[62] Shao Mingwen*, Leung Yee, Wu Weizhi, Rule Acquisition and Complexity Reduction in Formal Decision Contexts, International Journal of Approximate Reasoning, 2014, 55(1): 259-274. ( SCI 3区)

[63] Shao Mingwen*, Leung Yee, Relations between granular reduct and dominance reduct in formal contexts, Knowledge-Based Systems, 2014, 65: 1-11. ( SCI 1区)

[64] Shao Mingwen*, Yang hongzhi. Two kinds of multi-level formal concepts and its application for sets approximations, International Journal of Machine Learning and Cybernetics, 2013, 4(6): 621-630. (SCI 3区 )

[65] Shao Mingwen*, Liu Min, Guo Li. Vector-based Attribute Reduction Method of the Concept Lattices, Fundamenta Informaticae, 2013,126(4): 397-414. (SCI 4区)

[66] Wu Weizhi, Leung Yee, Shao Mingwen. Generalized fuzzy rough approximation operators determined by fuzzy implicators, International Journal of Approximate Reasoning, 2013, 54(9): 1388-1409. (SCI 3区 )

[67] 邵明文, 伍席文, 郭理. 数据变化与概念格结构的关系,工程数学学报, 2012, 29(4): 529-539.

[68] Yang Hongzhi, Leung Yee, Shao Mingwen*. Rule Acquisition and Attribute Reduction in Real Decision Formal Contexts. Soft Computing, 2011, 11:1115-1128. (SCI 3区 )

[69] Shao Mingwen*, Guo Li, Li Lan. A novel attribute reduction approach based on the object oriented concept lattice, Lecture Notes in Computer science, 2011, Vol. 6954: 71-80.

[70] Shao Mingwen*, Liu Min, Zhang Wenwiu. Set approximations in fuzzy formal concept analysis. Fuzzy Set and Systems, 2007, 158 : 2627-2640. (SCI 1区 )

[71] Liu Min, Shao Mingwen*, Zhang Wenxiu. Reduction method for concept lattices based on rough set theory and its application. Computer & Mathematics with Applications, 2007, 53: 1390-1410. (SCI 2区 )

[72] Shao Mingwen*, Zhang Wenxiu. Approximation in Formal Concept Analysis. Lecture Notes in Computer science, 2005, Vol. 3641: 43-53. (SCI收录)

[73] Shao Mingwen*, Zhang Wenxiu. Dominance Relation and Rules in An Incomplete Ordered Information System. International Journal of Intelligent Systems, 2005, 20(1): 13-27. (SCI 2区)

[74] 邵明文, 张文修, 米据生. 合成信息系统与子信息系统. 计算机科学, 2004, 3: 137-140.

2007年获省教育厅高校青年骨干教师称号

自2006年以来共指导培养硕士研究生毕业20余名；目前，在读博士研究生4名、硕士研究生16名。