张蒙蒙 电话：010-68918217
副研究员 邮箱：mengmengzhang@bit.edu.cn
北京理工大学信息与电子学院 地址：北京理工大学信息科学实验楼510房间
信息与通信工程
多源遥感图像处理
2020.01 至今：任职于 北京理工大学 信息与电子学院 副研究员
2014.09-2019.12：就读于 北京化工大学 控制科学与工程专业 博士
2010.09-2014.07：就读于 青岛科技大学 计算机科学与技术专业 本科
长期从事多源遥感图像处理方向相关理论方法及工程应用研究，主持国家自然科学基金面上项目、青年科学基金项目、博士后创新人才支持计划、北京市自然科学基金面上项目等，入选北京市科协“青年人才托举工程”，获中国电子学会自然科学一等奖等。发表学术论文80余篇，授权/受理发明专利10余项，部分学术成果如下：
[1] M. Zhang, Y. Zhao, R. Chen, Y. Gao*, Z. Li and W. Li, “Remote Sensing Collaborative Clas sification Using Multimodal Adaptive Modulation Network,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-12, Art no. 5529512, 2024.
[2] M. Zhang, C. Guo, Y. Zhang*, H. Liu and W. Li, “GCCD: A Generative Cross-Domain Change Detection Network,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-10, Art no. 5628410, 2024.
[3] H. Wang, M. Zhang*, W. Li, Y. Gao, Y. Gui and Y. Zhang, “Unbalanced Class Learning Network With Scale-Adaptive Perception for Complicated Scene in Remote Sensing Images Segmentation,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-12, Art no. 4406712, 2024.
[4] B. Zhao, M. Zhang*, W. Li, X. Song, Y. Gao, Y. Zhang and J. Wang, “Intermediate Domain Prototype Contrastive Adaptation for Spartina alterniflora Segmentation Using Multitemporal Remote Sensing Images,” in IEEE Transactions on Geoscience and Remote Sensing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-14, Art no. 5401314, 2024.
[5] Y. Tian, M. Zhang*, J. Li, Y. Li, H. Yang and W. Li, “FPNFormer: Rethink the Method of Processing the Rotation-Invariance and Rotation-Equivariance on Arbitrary-Oriented Object Detection,” IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-10, Art no. 5605610, 2024.
[6] M. Zhang, X. Zhao, W. Li∗, Y. Zhang, R. Tao, and Q. Du, “Cross-Scene Joint Classif ication of Multisource Data with Multi-level Domain Adaption Network,” IEEE Transactions on Neural Network and Learning Systems, vol. 35, no. 8, pp. 11514-11526, 2024.
[7] X. Zhao, M. Zhang∗#, R. Tao, W. Li, W. Liao, L. Tian, and W. Philips, “Fractional Fourier Image Transformer for Multimodal Remote Sensing Data Classification,” IEEE Transactions on Neural Network and Learning Systems, vol. 35, no. 2, pp. 2314-2326, 2024.
[8] X. Zhao, M. Zhang∗#, W. Li, K Gao and R Tao, “A sparse representation and Cauchy distance combination graph for hyperspectral target detection”, Remote Sensing Letters, vol.14, no. 11, pp:1218-1226, 2023.
[9] J. Wang, M. Zhang*, W. Li and R. Tao, “A Multistage Information Complementary Fusion Network based on Flexible-Mixup for HSI-X Image Classification,” IEEE Transactions on Neural Networks and Learning Systems, in print, 2023.
[10] Y. Gao, M. Zhang*, W. Li, X. Song, X. Jiang and Y. Ma, “Adversarial Complementary Learning for Multisource Remote Sensing Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-13, Art no. 5505613, 2023.
[11] M. Zhang, W. Li∗, Y. Zhang, R. Tao, and Q. Du, “Hyperspectral and LiDAR Data Classi f ication Based on Structural Optimization Transmission,” IEEE Transactions on Cybernetics, vol. 53, no. 5, pp. 3153-3164, 2023.
[12] Y. Zhang, M. Zhang∗, W. Li, S. Wang, and R. Tao, “Language-Aware Domain Generaliza tion Network for Cross-Scene Hyperspectral Image Classification,” IEEE Transactions on Geo science and Remote Sensing, vol. 61, pp. 1-12, Art no. 5501312, 2023.
[13] M. Zhang, W. Li∗, X. Zhao, H. Liu, R. Tao, and Q. Du, “Morphological Transformation and Spatial-Logical Aggregation for Tree Species Classification Using Hyperspectral Imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-12, Art no. 5501212, 2023.
[14] M. Zhang, W. Li, R. Tao, H. Li, and Q. Du, “Information Fusion for Classification of Hy perspectral and LiDAR Data Using IP-CNN,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-12, Art no. 5506812, 2022.
[15] Z. Guo, M. Zhang∗, W. Jia, J. Zhang, and W. Li, “Dual-Concentrated Network with Mor phological Features for Tree Species Classification Using Hyperspectral Image,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 7013-7024, 2022
[16] X. Zhao, M. Zhang∗#, R. Tao, W. Li, W. Liao, and W. Philips, “Cross-Domain Classifica tion of Multisource Remote Sensing Data Using Fractional Fusion and Spatial-Spectral Domain Adaption,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sens ing, vol. 15, pp. 5721-5733, 2022.
[17] X. Yang, M. Zhang∗, W. Li, and R. Tao, “Visible-Assisted Infrared Image Super-Resolution Based on Spatial Attention Residual Network,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, Art no. 7002705, 2022.
[18] Y. Zhu, W. Li, M. Zhang∗, Y. Pang, R. Tao, and Q. Du, “Joint Feature Extraction for Multi-Source Data Using Similar Double-Concentrated Network,” Neurocomputing, vol. 450, pp. 70-79, August 2021.
[19] M. Zhang, W. Li∗, R. Tao, and S. Wang, “Transfer Learning for Optical and SAR Data Corresponding Identification with Limited Training Labels,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1545-1557, January 2021.
[20] D. Cao, M. Zhang∗, W. Li, and Q. Ran, “Hyperspectral and Infrared Image Collaborative Classification Based on Morphology Feature Extraction,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 4405-4416, April 2021.
[21] X. Zhao, W. Li, M. Zhang∗, R. Tao, P. Ma, and Z. Cai, “Adaptive Iterated Shrinkage Thresh olding based Lp-norm Sparse Representation for Hyperspectral Imagery Target Detection,” Remote Sensing, vol. 12, no. 23：3991, DOI: 10.3390/rs12233991, December 2020.
[22] M. Zhang, W. Li∗, Q. Du, L. Gao, and B. Zhang, “Feature Extraction for Classifica tion of Hyperspectral and LiDAR Data Using Patch-to-Patch CNN,” IEEE Transactions on Cybernetics, vol. 50, no. 1, pp. 100-111, January 2020.[23] W. Li, C. Chen, M. Zhang∗, H. Li, and Q. Du, “Data Augmentation for Hyperspectral Image Classification with Deep CNN,” IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 4, pp. 593-597, April 2019.
[23] W. Li, C. Chen, M. Zhang∗, H. Li, and Q. Du, “Data Augmentation for Hyperspectral Image Classification with Deep CNN,” IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 4, pp. 593-597, April 2019.
[24] M. Zhang, W. Li∗, and Q. Du, “Diverse Region-Based CNN for Hyperspectral Image Classi f ication,” IEEE Transactions on Image Processing, vol. 27, no. 6, pp. 2623-2634, June 2018.
[25] M. Zhang, W. Li∗, and Q. Du, “Collaborative Classification of Hyperspectral and Visible Images with Convolutional Neural Network,” Journal of Applied Remote Sensing, vol. 11, no. 4, article ID 042607, September 2017.
[26] M. Zhang, P. Ghamisi, and W. Li∗, “Classification of Hyperspectral and LiDAR Data Using Extinction Profiles with Feature Fusion,” Remote Sensing Letters, vol. 8, no. 10, pp. 957-966, June 2017.
[27] 张蒙蒙，李伟，基于形态变换与空间逻辑聚合的高光谱森林树种分类，测绘学报，52(7)，1202 1211，2023.
[1] 面向林地资源监测的多源遥感跨域协同分类关键技术研究，国家自然科学基金面上基金项目，负责人
[2] 高光谱与激光雷达数据融合及协同分类技术研究，国家自然科学基金青年基金项目，负责人
[3] 基于多元差异性分析的多源遥感协同观测理论与方法研究，博士后创新人才支持计划，负责人
[4] 基于多层级不确定性联合控制及深度学习的高光谱精细分类方法研究，北京市自然科学基金面上基金项目，负责人
[5] 基于高光谱与激光雷达数据联合分析的地物分类方法研究, 中国博士后基金面上项目, 负责人
[6] 复杂背景下遥感伪装目标光谱实时探测方法，天基智能信息处理全国重点实验室开放基金，负责人
[1] 电子学会自然科学一等奖，2022年
[2] 博新计划优秀创新成果奖，2020年
[3] 测绘科学技术二等奖，2021年
[4] 山东省自然资源科学技术二等奖，2024年
[5] 北京市青年人才托举工程，2024年
[6] 全球前2%顶尖科学家，2024年
[7] 第六届全国成像光谱对地观测学术研讨会(行业顶会)优秀报告，2023年
[8] 第五届“中科星图杯”国际高分遥感图像解译大赛冠军，指导老师，2023年
[9] 北京理工大学本原基金专项奖，2023年
[10] “师缘·北理”第39个教师节学术创新类表彰，2023年
[11] “Best Presentation Award”– The 7th International Conference on lmage and Graphics Pro cessing (lCIGP 2024)，指导老师，2024年
[12] 人口健康共享杯大赛一等奖，指导老师，2024年
[13] 北京理工大学优秀博士后，2021年
[1]《人工智能导论》
[2]《机器学习理论与实践》
