机器学习、计算机视觉

近期主要工作：图像/视频生成与编辑，图像恢复，3D视觉，视觉大模型等。

《机器学习》、《数据挖掘》、《模式识别》

1.        国家自然科学基金项目（No：62376285），“多种恶劣天气下的退化图像一体化恢复方法研究”，2024.01-2027.12，主持；

2.        智能制造福建省高校应用技术工程中心开放课题，“基于少样本增量学习的元学习方法研究”，2023.10-2024.10，主持；

3.        上市公司横向技术开发课题，“恶劣天气红外视频增强解决方案”，2023.06-2024.06, 25万，主持；

4.        上市公司横向技术开发课题，“红外视频超分解决方案，2023.06-2024.06, 25万，主持；

5.        智能制造福建省高校应用技术工程中心开放课题，“基于自监督学习与图像重构的生成对抗网络设计”，2022.12-2023.12，主持；

6.        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；

7.        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；

8.        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；

9.        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；

10.    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；

11.    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；

12.    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；

13.    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；

14.    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；

15.    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；

16.    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；

17.    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；

18.    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。

19.    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。

近年发表的主要学术论文 (Selected Journal Papers)：

DBLP：https://dblp.org/pid/97/6241.html

Researchgate：https://www.researchgate.net/profile/Mingwen-Shao/publications

1.      Liu Yuexian, Shao Mingwen*, Cheng Yuanshuo, Wan Yecong, Han Minggui, Cross-domain attention-guided domain adaptive method for image real rain removal, Multimedia Tools and Applications, 2024, https://DOI.10.1007/s11042-024-19006-0. (SCI 3区)

2.      Meng Lingzhuang, Shao Mingwen*, Wang Fan, Qiao Yuanjian, Xu Zhaofei, Advancing Few-Shot Black-Box Attack with Alternating Training, IEEE Transactions on Reliability, 2024, https://DOI.10.1109/TR.2024.3369865. (SCI 2区)

3.      Shao Mingwen, Kuang Jiandong, Wang Chao*, Zuo Wangmeng, Wang Guoyin, Multi-Dimensional Dynamic Pruning: Exploring Spatial and Channel Fuzzy Sparsity, IEEE Transactions on Fuzzy Systems, 2024, https://doi.org/10.1109/ TFUZZ.2024.3363220.  (SCI 1区)

4.      Kai Shang, Shao Mingwen*, Wang Chao, Cheng Yuanshuo, Wang Shuigen, Multi-Domain Multi-Scale Diffusion Model for Low-Light Image Enhancement, AAAI 2024. （CCF A）

5.      Shao Mingwen*, Bao Zhiyuan, Liu Weihan, Qiao Yuanjian, Wan Yecong, Frequency Domain Enhanced Transformer for Single Image Deraining, The Visual Computer, 2024, https://doi.org/10.1007/s00371-023-03252-8.  (SCI 3区)

6.      Li Le, Pan Hudan, Liang Yong, Mingwen Shao, Xie Shengli, Lu Shanghui, PMFN-SSL: Self-supervised learning-based progressive multimodal fusion network for cancer diagnosis and prognosis, Knowledge-Based Systems, 2024, 111502. (SCI 1区)

7.      Wang Leiquan, Fang Ye, Li Zhongwei, Wu Chunlei, Xu Mingming, Mingwen Shao, Summator–Subtractor Network: Modeling Spatial and Channel Differences for Change Detection, IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 5604212.  (SCI 1区)

8.      Wang Fan, Shao Mingwen*, Dual Stage Black-box Adversarial Attack against Vision Transformer, International Journal of Machine Learning and Cybernetics, 2024, https://doi. org/10.1007/s13042-024-02097-4. (SCI 3区)

9.      Han Minggui, Shao Mingwen*, Meng Lingzhuang, Liu Yuexian, and Qiao Yuanjian, Multilevel contrast strategy for unpaired image-to-image translation, Journal of Electronic Imaging, 2024, 32(6): 063030.(SCI 4区)

10.  Mingwen Shao, Peng Zilu*, Distance metric-based learning for long-tail object detection, Image and Vision Computing, 2023, https://doi.org/10.1016/j.imavis. 2023.104888.  (SCI 3区)

11.  Wang Leiquan, Wang Yunfeng, Li Zhongwei, Wu Chunlei, Xu Mingming, Mingwen Shao, Eliminating Spatial Correlations of Anomaly: Corner-Visible Network for Unsupervised Hyperspectral Anomaly Detection. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 1-14.  (SCI 1区)

12.  Kai Shang, Shao Mingwen *, Qiao Yuanjian, Liu Huan, Frequency-aware Network for Low-light Image Enhancement, Computers & Graphics, 2023, https://doi. org/10.1016/j.cag.2023.12.014. (SCI 3区)

13.  Mingwen Shao, Yang Jianxin, Meng Lingzhuang*, Hu Zhiyong, Frequency Attacks Based on Invertible Neural Networks, IEEE Transactions on Artificial Intelligence, 2023, https://doi.org/10.1109/TAI.2023.3349238.

14.  Hu Zhiyong, Mingwen Shao*, Mi Jusheng, Wu Weizhi, Mining Positive and Negative Rules via One-sided Fuzzy Three-way Concept Lattices, Fuzzy Sets and Systems, 2024: 108842. https://doi.org/10.1016/j.fss.2023.108842. (SCI 1区)

15.  Zhang Jie, Shao Mingwen*, Qiao Yuanjian, Cao Xiangyong, Enhancing Efficient Global Understanding Network with CSWin Transformer for Urban Scene Images Segmentation, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, accepted.  (SCI 2区)

16.  Bao Zhiyuan, Shao Mingwen*, Wan Yecong, Qiao Yuanjian, Recursive Residual Fourier Transformation for Single Image Deraining, International Journal of Machine Learning and Cybernetics, 2023, https://doi.org/10.1007/s13042-023-01994-4.  (SCI 3区)

17.  Chen Sijie, Shao Mingwen*, Zhang Lixu, Bao Zhiyuan, Two-stage structural information enhancement for source-free domain adaptation, Machine Vision and Applications, 2023, https://doi.org/10.1007/s00138-023-01472-5. (SCI 4区)

18.  Zhang Lixu, Shao Mingwen*, Chen Sijie, Liu Fukang, Contrastive knowledge-augmented self-distillation approach for Few-Shot Learning, Journal of Electronic Imaging, 2023, 32(5): 053037. https://doi.org/10.1117/1.JEI.32.5.053037(SCI 4区)

19.  Shao Mingwen*, Liu Fukang, Guo Zihao, Qiao Yuanjian, Hairstyle transfer via manipulating decoupled latent codes of StyleGAN2, Computers & Graphics, 2023，16: 363–372. (SCI 3区)

20.  Li Le, Liang Yong, Shao Mingwen, Lu Shanghui, liao Shuilin, Dong Ouyang: Self-supervised learning-based Multi-Scale feature Fusion Network for survival analysis from whole slide images. Comput. Biol. Medicine, 2023, 153: 106482. (SCI 2区)

21.  Cheng Yuanshuo, Shao Mingwen*, Wan Yecong, Mutually Guided Learning of Global Semantics and Local Representations for Image Restoration, Multimedia Tools and Applications, 2023, https://doi.org/10.1007/s11042-023-16724-9.  (SCI 3区)

22.  Wan Yecong, Shao Mingwen*, Cheng Yuanshuo, Ding Weiping，Fuzzy-based Cross-Image Pixel Contrastive Learning for Compact Medical Image Segmentation,Multimedia Tools and Applications, 2023, https://doi.org/10.1007/s11042-023-16611-3.  (SCI 3区)

23.  Qiao Yuanjian, Shao Mingwen*, Wang Leiquan, Zuo Wangmeng, Learning Depth-Density Priors for Fourier-based Unpaired Image Restoration, IEEE Transactions on Circuits and Systems for Video Technology, 2023, https://doi.org/10.1109/ TCSVT.2023.3305996.  (SCI 1区)

24.  Hua Zhiyong, Shao Mingwen*, Wu Weizhi, Li Leijun, Knowledge acquisition of multi-granularity ordered information systems, Applied Soft Computing, 2023, https://doi.org/10.1016/j.asoc.2023.110674.  (SCI 1区)

25.  Wang Leiquan, Wang Yunfeng, Li Zhongwei, Wu Chunlei, Xu Mingming, Shao Mingwen, Eliminating Spatial Correlations of Anomaly: Corner-Visible Network for Unsupervised Hyperspectral Anomaly Detection. IEEE Transactions on Geoscience and Remote Sensing, 2023: 61: 1-14. (SCI 1区)

26.  Liu Huan, Shao Mingwen*, Qiao Yuanjian, Wan Yecong, Meng Deyu, Unpaired Image Super-resolution Using a Lightweight Invertible, Pattern Recognition, 2023，144: 109822. https://doi.org/10.1016/j.patcog.2023.109822.  (SCI 1区)

27.  Shao Mingwen, Liu Huan*, Yang Jianxin, Cao Feilong, An Adaptive One-stage Generative Adversarial Network for Unpaired Image Super-resolution, 2023, Neural Computing and Applications, 2023, https://doi.org/10.1007/s00521-023-08888-0.    (SCI 2区)

28.  Wan Yecong, Shao Mingwen*, Cheng Yuanshuo, Meng Deyu, Zuo Wangmeng, Progressive Convolutional Transformer for Image Restoration, Engineering Applications of Artificial Intelligence, 2023, 125: 106755.  (SCI 2区)

29.  Cheng Yuanshuo, Shao Mingwen*, Wan Yecong, Liu Yuexian, Liu Huan, Meng Deyu, Deep Fuzzy Clustering Transformer: Learning the General Property of Corruptions for Degradation-Agnostic Multi-Task Image Restoration, IEEE Transactions on Fuzzy Systems, 2023, 31(12): 4501-4515. (SCI 1区)

30.  Liu Fukang, Shao Mingwen*, Wang Fan, Zhang Lixu, High-fidelity GAN inversion by frequency domain guidance, Computers & Graphics, 2023, 114: 286-295.  (SCI 3区)

31.  Wan Yecong, Shao Mingwen*, Bao Zhiyuan, Cheng Yuanshuo, Global-local Transformer for Single Image Rain Removal, Pattern Analysis and Applications, 2023, DOI: 10.1007/s10044-023-01184-6.  (SCI 4区)

32.  Shao Mingwen*, Li Shunhang*, Peng Zilu, Sun Yuantao, Adversarial-based Ensemble Feature Knowledge Distillation, Neural Process Letter, 2023, https://doi.org/10.1007/s11063-023-11328-8. (SCI 3区)

33.  Zhang Junsan, Feng Yeqi, Wang Chao, Shao Mingwen, Jiang Yujie, Wang Jian, Multi-domain clustering pruning: Exploring space and frequency similarity based on GAN, Neurocomputing, 2023, 542:126279.  (SCI 2区)

34.  Qiao Yuanjian, Shao Mingwen*, Liu Huan, Shang Kai, Mutual channel prior guided dual-domain interaction network for single image raindrop removal, Computers & Graphics, 2023, 112:132–142.  (SCI 3区)

35.  Shao Mingwen, Sun Yuantao*, Liu Zeting, Peng Zilu, Li Shunhang, Li Cunhe, GPNet: Key Point Generation Auxiliary Network for Object Detection, Advanced Theory and Simulations, 2023, 4:2200894. https://doi.org/10.1002/adts.202200894. (SCI 3区)

36.  Li Shunhang, Shao Mingwen*, Guo Zihao, Zhuang Xinkai, Improving knowledge distillation via pseudo-multi-teacher network, Machine Vision and Applications, 2023, 34:33. https://doi.org/10.1007/s00138-023-01383-5.  (SCI 4区)

37.  Guo Zihao, Shao Mingwen*, Li Shunhang, Image-to-image translation using an offset-based multi-scale codes GAN encoder, The Visual Computer, 2023, https://doi.org/10.1007/s00371-023-02810-4.   (SCI 3区)

38.  Shao Mingwen, Zhiyong Hu*, Wu Weizhi, Liu Huan, Graph Neural Networks Induced by Concept Lattices for Classification, International Journal of Approximate Reasoning, 2023, 154:262-276.  (SCI 2区)

39.  Shao Mingwen, QiaoYuanjian*, Meng Deyu, Zuo Wangmeng, Uncertainty-Guided Hierarchical Frequency Domain Transformer for Image, Knowledge-Based Systems, 2023, 262:110306.  (SCI 1区)

40.  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, 2023, 14:2499–2509.  (SCI 3区)

41.  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)

42.  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)

43.  Liu Zeting, Shao Mingwen*, Sun Yuantao, Peng Zilu, Multi-task feature-aligned head in one-stage object detection, Signal, Image and Video Processing, 2023, 17: 1345–1353.  (SCI 4区)

44.  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)

45.  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 1区)

46.  Shao Mingwen*, Zhang Wei, Li Yunhao, Fan Bingbing, Branch Aware Assignment for Object Detection, Visual Computer, 2023, 39, 5719–5728 https://doi. org/10.1007/s00371-022-02691-z.  (SCI 3区)

47.  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)

48.  Liu Huan, Shao Mingwen*, Wang Chao, Cao Feilong, Image Super-Resolution Using a Simple Transformer without Pre-training, Neural Processing Letters, 2023, 55:1479-1497.  https://doi.org/10.1007/s11063-022-10948-w.  (SCI 3区)

49.  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)

50.  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)

51.  Wan Yecong, Cheng Yuanshuo, Shao Mingwen*, MSLANet: Multi-scale Long Attention Network for Skin Lesion Classication, Applied Intelligence, 2023:53:12580–12598.    (SCI 2区)

52.  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)

53.  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)

54.  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)

55.  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)

56.  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)

57.  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)

58.  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)

59.  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)

60.  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)

61.  Shao Mingwen*, Wang Chao, 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)

62.  Hu Zhiyong, Shao Mingwen*, Liu Huan, Mi Jusheng, Cognitive Computing and Rule Extraction in Generalized One-sided Formal Contexts, Cognitive Computing,2022,14: 2087–2107.  (SCI 2区)

63.  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)

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

65.  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)

66.  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)

67.  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)

68.  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)

69.  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)

70.  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)

71.  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)

72.  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)

73.  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 1区)

74.  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)

75.  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)

76.  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)

77.  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)

78.  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 1区)

79.  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)

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

81.  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 2区)

82.  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 1区，SCI高被引论文)

83.  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)

84.  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)

85.  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)

86.  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)

87.  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)

88.  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 1区)

89.  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)

90.  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)

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

92.  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)

93.  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)

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

95.  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)

96.  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 1区)

97.  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 1区)

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

99.  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 2区)

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

101.              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)

102.              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)

103.              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 1区)

104.              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.

105.              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)

106.              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.

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

108.              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)

109.              ShaoMingwen*, Zhang Wenxiu. Approximation in Formal Concept Analysis. Lecture Notes in Computer science, 2005, Vol. 3641: 43-53.  (SCI收录)

110.              ShaoMingwen*, 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)

111.              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

每年招收硕士生4-7名，博士生1-2名，欢迎喜欢科学研究或专注于机器视觉最前沿技术开发的同学加入团队，一起学习。另外，欢迎本校优秀本科生加入我们团队。