| 科研成果: |
科研项目 1、国家自然科学基金青年项目,基于深度迁移学习网络的高分影像土地利用分类方法研究,41801324,2019/01-2021/12,主持,已结题。 2、福建省自然科学基金面上项目,人机协同的自然资源要素提取关键技术研究,2023J01432,2023/08-2026/08,主持。 3、福建省自然科学基金面上项目,基于深度迁移学习的高分影像土地利用分类研究,2019J01244,2019/06-2022/7,主持,已结题。 4、福建省教育厅中青年项目,基于深度学习的高分影像土地利用分类方法研究,JAT160087,2016/12-2017/12,主持,结题。 5、国家自然科学基金青年基金项目“基于深度信念网络的高光谱遥感影像变化检测方法研究” 41501451,参与.
近年发表的主要论文 1、Weng, Q.; Huang, X.; Lin, Y.; Zhang, Y.; Li, Z.; Jian, C.; Lin, J. GIMMNet: Geometry-Aware Interactive Multi-Modal Network for Semantic Segmentation of High-Resolution Remote Sensing Imagery. Remote Sens. 2026, 18, 124. https://doi.org/10.3390/rs18010124 ( JCR Q1,2023级研究生黄贤圣为第二作者 ) 2、Weng, Q.; Wang, Q.; Lin, Y.; Lin, J. ARE-Net: An Improved Interactive Model for Accurate Building Extraction in High-Resolution Remote Sensing Imagery. Remote Sens. 2023, 15, 4457. https://doi.org/10.3390/rs15184457(JCR Q1,2021级研究生王钦为第二作者) 3、Q. Weng, Z. Huang, J. Lin, C. Jian and Z. Mao, "Remote Sensing Scene Classification Via Multigranularity Alternating Feature Mining," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 318-330, 2023, doi: 10.1109/JSTARS.2022.3225791. ( JCR Q1,2020级研究生黄志铭为第二作者) 4、Weng Q, Chen H, Chen H, et al. A Multisensor Data Fusion Model for Semantic Segmentation in Aerial Images[J]. IEEE Geoscience and Remote Sensing Letters, 2022. (JCR Q1,2020级研究生陈浩为第二作者) 5、Weng Q, Mao Z , Lin J , et al. Land-use scene classification based on a CNN using a constrained extreme learning machine[J]. International Journal of Remote Sensing, 2018, 39(19):6281-6299.(JCR Q2) 6、Weng Q, Mao Z , Lin J , et al. Land-Use Classification via Extreme Learning Classifier Based on Deep Convolutional Features[J]. IEEE Geoence and Remote Sensing Letters, 2017, PP(5):1-5. (JCR Q1) 7、Jia-Wen, Lin,Qian Weng, et al. A retinal image sharpness metric based on histogram of edge width[J]. Journal of Algorithms & Computational Technology, 2017. 8、翁谦,陈耿葳,潘增滢,林嘉雯,郑向涛.XXXX.AFMamba: Mamba架构下的高光谱与LiDAR自适应融合分类网络.遥感学报,XX(XX): 1-15 DOI: 10.11834/jrs.20254539.(2023级研究生陈耿葳为第二作者) 9、潘增滢,吴瑞姣,林易丰,等.改进的残差式3D-CNN和近邻注意力的高光谱遥感图像分类[J].自然资源遥感, 2025, 37(5):101-112.(2022级研究生潘增滢为第一作者),论文获2024年度《自然资源遥感》优秀论文奖; 10、翁谦,安远,陈光剑,吴瑞姣,林嘉雯.2025.结合空谱结构与改进局部密度的高光谱图像波段选择.遥感学报,29(1): 247-265 DOI: 10.11834/jrs.20243227.(EI期刊,2021级研究生安远为第二作者) 11、林易丰,陈光剑,陈浩, 翁谦,林嘉雯.面向多源数据的多区域尺度协同高分遥感图像语义分割[J].小型微型计算机系统,2025,46(1): 158-166(2022级研究生林易丰为第一作者) 12、翁谦,黄志铭,林嘉雯,简彩仁,廖祥文.多层次自适应知识蒸馏的轻量化高分遥感场景分类[J].福州大学学报(自然科学版),2023,第51卷(4): 459-466 (2020级研究生黄志铭为第二作者) 13、陈波, 翁谦, 叶少珍. 改进生成对抗网络的图像超分辨率重建算法[J]. 福州大学学报(自然科学版), 2021, 49(3):7. 14、蔡之灵,翁谦,叶少珍,简彩仁.基于Inception-V3模型的高分遥感影像场景分类[J].国土资源遥感,2020,32(03):80-89. 15、郭峰, 毛政元, 邹为彬,翁谦. 融合LiDAR数据与高分影像特征信息的建筑物提取方法[J]. 地球信息科学学报, 2020, 22(8): 1654-1665. 16、简彩仁,翁谦, 陈晓云. 基于核最小二乘回归子空间分割的高维小样本数据聚类[J]. 福州大学学报(自然科学版), 2018, v.46;No.221(01):41-47+54. 17、杨进一, 徐伟铭, 王成军,翁谦. 基于超像元词包特征和主动学习的高分遥感影像变化检测[J]. 地球信息科学学报, 2019, 21(10). 18、王成军, 毛政元, 徐伟铭,翁谦. 超像素与主动学习相结合的遥感影像变化检测方法[J]. 地球信息科学学报, 2018, 20(002):235-245. 19、翁谦,毛政元,林嘉雯,简彩仁,应用谱回归和图正则最小二乘回归的数据降维[J],计算机工程与应用,2017, 53(5): 81-84. 20、简彩仁,翁谦.基于局部强化最小二乘回归子空间分割的基因表达数据聚类[J].三明学院学报,2016,33(06):1-7.
会议论文: 1、Y. Ye, H. Xu, Y. Huang, J. Huang and Q. Weng*, "PreSem-Surf: RGB-D Surface Reconstruction with Progressive Semantic Modeling and SG-MLP Pre-Rendering Mechanism," 2025 International Joint Conference on Neural Networks (IJCNN), Rome, Italy, 2025, pp. 1-8, doi: 10.1109/IJCNN64981.2025.11228530.(CCF-C类会议, 2022级软件工程本科生叶宇滟为第一作者) 2、X. Huang, J. Lin, C. Jian, Q. Wang and Q. Weng*, "SDFCNet: A Spatial-Domain and Frequency-Domain Collaborative Network for Building Extraction in High-Resolution Remote Sensing Images," 2025 IEEE International Conference on Image Processing (ICIP), Anchorage, AK, USA, 2025, pp. 223-228, doi: 10.1109/ICIP55913.2025.11084460. (已录用,EI,CCF-C会议,2024级研究生黄贤圣为第一作者) 3、Chen, M., Weng, Q*., Zeng, C., Lin, J., Kang, Y.Time-Frequency Feature Enhancement Method for Moving Multiple Sound Source Localization in Noisy Environments[C]//International Conference on Intelligent Computing.Springer, Singapore, 2025.DOI:10.1007/978-981-96-9805-9_31, Oral论文(已录用,EI,CCF-C会议,2023级研究生陈模为第一作者,系与厦门亿联公司联合指导工作成果) 4、Zhang, Y., Zhang, Y., Jian, C., Weng, Q*.Mamba-OSCDNet: A Mamba-Based Siamese Network with Cross-Attention Fusion and Contrastive Learning for Optical-SAR Change Detection[C]//International Conference on Intelligent Computing.Springer, Singapore, 2025.DOI:10.1007/978-981-96-9952-0_7.Oral论文(已录用,EI,CCF-C会议,2023级研究生张滢滢为第一作者) 5、Qian Weng, Yifeng Lin*,Zengying Pan, Jiawen Lin, Gengwei Chen, Mo chen, Yingying Zhange. BFRNet: Bimodal Fusion and Rectification Network for Remote Sensing Semantic Segmentation;The 7th Chinese Conference on Pattern Recognition and Computer Vision PRCV 2024(CCF推荐C类会议),2024. (已录用,EI,2022级研究生林易丰为第二和通讯作者) 6、Pan Zengying, Wu Ruijiao, Chen Gengwei, Jian Cairen, Weng Qian*. Extraction of Rice Planting Range Based on Hyperspectral Data of ZY-1 02E, 2024 International Conference on Image Processing, Intelligent Control and Computer Engineering (IPICE), 2024.(已录用,EI,2022级研究生潘增滢为第一作者) 7、Yuan An, Guangjian Chen, Dehua Huang, Huiqin Zheng, Qin Wang, Cairen Jian, Qian Weng. A Hyperspectral Band Selection Network Combining Siamese Network and Local-Global Attention. IEEE 2023 13th International Conference on IT in Medicine and Education (ITME), 2023. (已录用,EI,2021级研究生安远为第一作者) 8、Z. Huang, Q. Weng, J. Lin and C. Jian, "Lightweight High-Resolution Remote Sensing Scene Classification via Adaptive Enhanced Knowledge Distillation," 2022 5th International Conference on Data Science and Information Technology (DSIT), 2022, pp. 1-6, doi: 10.1109/DSIT55514.2022.9943931. (EI,2020级研究生黄志铭为第一作者) 9、Wu Y, Weng Q, Lin J, et al. RA-ViT: Patch-wise Radially-Accumulate Module for ViT in Hyperspectral Image Classification[C]//Journal of Physics: Conference Series. IOP Publishing, 2022, 2278(1): 012009. (EI,2020级研究生吴雨阳为第一作者) 10、Cai Z L ,Weng Q, Ye S Z . RESEARCH ON SE-INCEPTION IN HIGH-RESOLUTION REMOTE SENSING IMAGE CLASSIFICATION[J]. 2020. |