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张良培\|个人主页 Prof. Liangpei Zhang\|Homepage
首页 Home 专业 Interests 学术 Publications 项目 Projects 荣誉 Honors 兼职 Activities 培养 Students 交流 Visitors	文章 Publications (Appeared in international journal) 英文部分（论文与学生合作完成,本人为通讯作者） • Xue, N., Wu, T., Xia, G.,..Zhang, L., 2023, Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning，IEEE Trans. on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2023.3312749. • Chen, D., Zhong Y., Ma, A., Zheng, Z., Zhang, L., 2023, Explicable Fine-Grained Aircraft Recognition Via Deep Part Parsing Prior Framework for High-Resolution Remote Sensing Imagery, IEEE Trans. on Cybernetics, Vol.12, DOI: 10.1109/TCYB.2023.3293033. • Wang, Y., Yuan, Q., Li, T., Yang, Y., Zhou, S., Zhang, L., 2023, Seamless mapping of long-term (2010-2020) daily global XCO2 and XCH(4) from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatio-temporally self-supervised fusion method，*EARTH SYSTEM SCIENCE DATA, Vol.15, Issue 8, P.3597-3622.e,* DOI: 10.5194/essd-15-3597-2023. • Zheng, Z., Zhong, Y., Wang, J., Ma, A., Zhang, L., 2022, FarSeg++: Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery，IEEE Trans. on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2023.3296757. • Wu, C., Du, B., Zhang, L., 2022, Fully Convolutional Change Detection Framework with Generative Adversarial Network for Unsupervised, Weakly Supervised and Regional Supervised Change Detection，IEEE Trans. on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2023.3237896. • Wan, Y., Zhong, Y., Ma, A., Wang, J., Zhang, L., 2022, E2SCNet: Efficient Multi-Objective Evolutionary Automatic Search for Remote Sensing Image Scene Classification Network Architecture，IEEE Trans. on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3220699. • Chen, C., Wan, Y., Ma, A., Zhang, L., Zhong, Y., 2022, A Decomposition-Based Multiobjective Clonal Selection Algorithm for Hyperspectral Image Feature Selection，IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2022.3216685. • Lu, X., Zhong, Y., Zhang, L., 2022, Open-Source Data-Driven Cross-Domain Road Detection from Very High Resolution Remote Sensing Imagery，IEEE Trans. On Image Processing, DOI: 10.1109/TIP.2022.3216481. • Zhang, Q., Yuan, Q., Song, M., Zhang, L., 2022, Cooperated Spectral Low-rankness Prior and Deep Spatial Prior for HSI Unsupervised Denoising，IEEE Trans. On Image Processing, DOI: 10.1109/TIP.2022.3211471. • Xu, Y., Du, B., Zhang, L., 2022, Robust Self-Ensembling Network for Hyperspectral Image Classification，IEEE Trans. on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3198142. • Wang, Y., Yuan, Q., Zhou, S., Zhang, L., 2022, Global spatiotemporal completion of daily high-resolution TCCO from TROPOMI over land using a swath-based local ensemble learning method，ISPRS Journal of Photogrammetry and Remote Sensing., Vol.194, PP.167–1, DOI: 10.1016/j.isprsjprs.2022.10.012. • Zhu, Q., Deng, W., Zhong, Y., Guan, Q., Zhang, L., Li, D., 2022, A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification,，IEEE Trans. on Cybernetics, Vol.11, No.11, PP. 11709-11723, DOI: 10.1109/TCYB.2021.3070577. • Wu, C., Chen, H., Du, B., Zhang, L., 2022, Unsupervised Change Detection in Multitemporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network,IEEE Trans. on Cybernetics,**DOI: 10.1109/TCYB.2021.3086884. • Tian, S., Zhong, Y., Zheng, Z., Ma, A., Tan, X., Zhang, L., 2022, Large-scale deep learning based binary and semantic change detection in ultra high resolution remote sensing imagery: From benchmark datasets to urban application, *ISPRS Journal of Photogrammetry and Remote Sensing,* DOI: 10.1016/j.isprsjprs.2022.08.012. • Chen, H., Zhang, H., Yang, G., Liu, S., 2022, A Mutual Information Domain Adaptation Network for Remotely Sensed Semantic Segmentation，*IEEE Trans. on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2022.3203910.* • Dong, Y., Shi, W., Du, B., Hu, X., Zhang, L., 2022, Asymmetric Weighted Logistic Metric Learning for Hyperspectral Target Detection，*IEEE Trans. on Cybernetics, Vol.50, No.10,* DOI: 10.1109/TCYB.2021.3070909. • Wan, Y., Ma, A., Zhang, L., Zhong, Y., 2022, Multiobjective Sine Cosine Algorithm for Remote Sensing Image Spatial-Spectral Clustering，*IEEE Trans. on Cybernetics, Vol.50, No.10,* DOI: 10.1109/TCYB.2021.3064552. • Li, Z., Zhang, H., Lu, F., Xue, R., Yang, G., Zhang, L., 2022, Breaking the resolution barrier: A low-to-high network for large-scale high-resolution land-cover mapping using low-resolution labels，*ISPRS Journal of Photogrammetry and Remote Sensing，Vol.192, PP. 244-267,* DOI: 10.1016/j.isprsjprs.2022.08.008. • Xiao, Y., Wang, Y., Yuan, Q., He, J., Zhang, L., 2022, Generating a long-term (2003−2020) hourly 0.25° global PM2.5 dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS)，*Science of the Total Environment, 848, 157747,* DOI: 10.1016/j.scitotenv.2022.157747. • Yang, K., Tong, X., Xia, G., Shen, W., Zhang, L., 2022, Hidden Path Selection Network for Semantic Segmentation of Remote Sensing Images，*IEEE Trans. on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2022.3197334.* • He, J., Yuan, Q., Li, J., Zhang, L., 2022, A Knowledge Optimization-Driven Network With Normalizer-Free Group ResNet Prior for Remote Sensing Image Pan-Sharpening，*IEEE Trans. on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2022.3186916.* • Zhu, D., Du, B., Dong, Y., Zhang, L., 2022, Spatial-Spectral Joint Reconstruction with Inter-band Correlation for Hyperspectral Anomaly Detection，*IEEE Trans. on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2022.3177510.* • Wan, Y., Zhong, Y., Ma, A., Zhang, L., 2022, An Accurate UAV 3-D Path Planning Method for Disaster Emergency Response Based on an Improved Multi-Objective Swarm Intelligence Algorithm，*IEEE Trans. on Cybernetics，DOI: 10.1109/TCYB.2022.3170580.* • Zhou, S., Yuan, Q., Yue, L., Zhang, L., 2022, Spatiotemporal estimation of 6-hour high-resolution precipitation across China based on Himawari-8 using a stacking ensemble machine learning model，*Journal OF Hydrology, Vol. 609, 127718, DOI:10.1016/j.jhydrol.2022.127718.* • Guo, Y., Wu, C., Du, B., Zhang, L., 2022, Density Map-based vehicle counting in remote sensing images with limited resolution，*ISPRS Journal of Photogrammetry and Remote Sensing，* DOI: 10.1016/j.isprsjprs.2022.05.004. • Wang, J., Ma, A., Zhong, Y., Zheng, Z., Zhang, L., 2022, Cross-sensor domain adaptation for high spatial resolution urban land-cover mapping: From airborne to spaceborne imagery, *Remote Sensing of Environment，* DOI: 10.1016/j.rse.2022.113058. • Song, Y., Zhang, H., Huang, H., Zhang, L., 2022, Remote Sensing Image Spatio-temporal Fusion via a Generative Adversarial Network with One Prior Image Pair, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2022.317133. • Lu, X., Zhong, Y., Zheng, Z., Chen, D., Su, Y., Ma, A., Zhang, L., 2022, Cascaded Multi-Task Road Extraction Network for Road Surface, Centerline, and Edge Extraction, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2022.3165817.* • Wang, S., Wang, X., Zhang, L., Zhong, Y., 2022, Deep Low-Rank Prior for Hyperspectral Anomaly Detection，*IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2022.3165833* • Lv, P., Wu, W., Zhong, Y., Du, F., Zhang, L., 2022, SCViT: A Spatial-Channel Feature Preserving Vision Transformer for Remote Sensing Image Scene Classification, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2022.315767. • Xu, H., He, W.，Zhang, L., Zhang, H., 2022, Unsupervised Spectral–Spatial Semantic Feature Learning for Hyperspectral Image Classification，IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2022.3159789. • Li, Z., Shen, H., Weng, Q., Zhang, Y., Dou, P., Zhang, L., 2022, Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects, ISPRS Journal of Photogrammetry and Remote Sensing，Vol.188, PP. 89–108,* DOI: 10.1016/j.isprsjprs.2022.03.020. • Zhao, H., Zhong, Y., Wang, X.,,,Zhang, L., 2022, Mapping the distribution of invasive tree species using deep one-class classification in the tropical montane landscape of Kenya，*ISPRS Journal of Photogrammetry and Remote Sensing，Vol.187, PP. 328–344,* DOI: 10.1016/j.isprsjprs.2022.03.005. • Ma, A., Yu, N., Zheng, Z., Zhong, Y., Zhang, L., 2022, A Supervised Progressive Growing Generative Adversarial Network for Remote Sensing Image Scene Classification, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2022.3151405. • Wu, J., Su, X., Yuan, Q., Shen, H., Zhang, L., 2022, Multivehicle Object Tracking in Satellite Video Enhanced by Slow Features and Motion Features, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3139121. • Shen, H., Qiu, Z., Yue, L., Zhang, L., 2022, Deep-Learning-Based Super-Resolution of Video Satellite Imagery by the Coupling of Multiframe and Single-Frame Models, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3121303. • Song, M., Zhong, Y., Ma, A., Xu, X., Zhang, L., 2022, A Joint Spectral Unmixing and Subpixel Mapping Framework Based on Multiobjective Optimization, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3132610.* • Zhu, Q., Lei, Y., Sun, X., Guan, Q., Zhong, Y., Zhang, L., Li, D., 2022，Knowledge-guided land pattern depiction for urban land use mapping: A case study of Chinese cities，*Remote Sensing of Environment 272，1129,* DOI: 10.1016/j.rse.2022.112916. • Xiao, J., Li, J., Yuan, Q., Zhang, L., A Dual-UNet With Multistage Details Injection for Hyperspectral Image Fusion, 2022, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3101848. • Liu, Z., Zhong, Y., Wang, X., Shu, M., Zhang, L., 2022, Unsupervised Deep Hyperspectral Video Target Tracking and High Spectral-Spatial-Temporal Resolution (H³) Benchmark Dataset，IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3111183.* • Zhang, L., Zhang, L., 2022, Artificial Intelligence for Remote Sensing Data Analysis, IEEE Geoscience and Remote Sensing Magazine, DOI:10.1109/MGRS.2022.3145854. • Feng, R., Li, H., Wang, L., Zhong, Y., Zhang, L., Zeng, T., 2022, Local Spatial Constraint and Total Variation for Hyperspectral Anomaly Detection, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3098814. • Liu, M., Shi, Q., Marinoni, A., He, D., Liu, X., Zhang, L., 2022, Super-Resolution-Based Change Detection Network With Stacked Attention Module for Images With Different Resolutions, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3091758. • Shi, Q., Liu, M., Li, S., Liu, X., Wang, F., Zhang, L., 2022, A Deeply Supervised Attention Metric-Based Network and an Open Aerial Image Dataset for Remote Sensing Change Detection, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3085870. • Dong, Y., Liu, Q., Du, B., Zhang, L., 2022, Weighted Feature Fusion of Convolutional Neural Network and Graph Attention Network for Hyperspectral Image Classification, IEEE Trans. On Image Processing,* *Vol.31, PP.1559-1572,* DOI: 10.1109/TIP.2022.3144017. • Cui, S., Ma, A., Zhang, L., Xu, M., Zhong, Y., 2022, MAP-Net: SAR and Optical Image Matching via Image-Based Convolutional Network With Attention Mechanism and Spatial Pyramid Aggregated Pooling, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3066432. • Li, T., Shen, H., Yuan, Q., Zhang, L., 2022, A Locally Weighted Neural Network Constrained by Global Training for Remote Sensing Estimation of PM₂.₅, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI:10.1109/TGRS.2021.3074569. • Zhu, Q., Guo, X., Guan, Q., Zhong, Y., Zhang, L., Li, D., 2022, Land-Use/Land-Cover change detection based on a Siamese global learning framework for high spatial resolution remote sensing imagery， ISPRS Journal of Photogrammetry and Remote Sensing, Vol.184, PP. 63-78,* DOI: 10.1016/j.isprsjprs.2021.12.005. • Zhang, H., Liu, W., Zhang, L., 2022, Seamless and automated rapeseed mapping for large cloudy regions using time-series optical satellite imagery, *ISPRS Journal of Photogrammetry and Remote Sensing, Vol.184, PP.45-62,* DOI: 10.1016/j.isprsjprs.2021.12.001. • Wang, X., Luo, Z., Liu, W., Hu, X., Zhang, L., Zhong, Y., 2022, A Self-Supervised Denoising Network for Satellite-Airborne-Ground Hyperspectral Imagery，*IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3064429.* • Hu, X., Zhong, Y., Wang, X., Luo, Zhao, J., Lei, L., Zhang, L., 2022, SPNet: Spectral Patching End-to-End Classification Network for UAV-Borne Hyperspectral Imagery With High Spatial and Spectral Resolutions, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI:10.1109/TGRS.2021.3049292.* • Zhao，S., Yuan, Q., Li, J., Hu, Y., Liu, X., Zhang, L., 2022, A Fast and Effective Irregular Stripe Removal Method for Moon Mineralogy Mapper (M3), *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3054661. • Wang, D., Du, B., Zhang, L., 2022, Fully Contextual Network for Hyperspectral Scene Parsing, IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2021.3050491.* • Shi, S., Zhong, Y., Zhao, J., Lv, P., Liu, Y., Zhang, L., 2022, Land-Use/Land-Cover Change Detection Based on Class-Prior Object-Oriented Conditional Random Field Framework for High Spatial Resolution Remote Sensing Imagery，*IEEE Trans. on Geoscience and Remote Sensing, Vol.60, DOI: 10.1109/TGRS.2020.3034373. • Guo, H., Du, B., Zhang, L., Su, X., 2022, A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery，ISPRS Journal of Photogrammetry and Remote Sensing, Vol.183, PP.240-252,* DOI: 10.1016/j.isprsjprs.2021.11.005. • Zheng, Z., Zhong, Y., Tian, S., Ma, A., Zhang, L., 2022, ChangeMask: Deep multi-task encoder-transformer-decoder architecture for semantic change detection, *ISPRS Journal of Photogrammetry and Remote Sensing, Vol.183, PP. 228-239,* DOI: 10.1016/j.isprsjprs.2021.10.015. • Zhai, H., Zhang, H., Zhang, L., 2022, Sparsity-Based Clustering for Large Hyperspectral Remote Sensing Images, IEEE Trans. on Geoscience and Remote Sensing, Vol.59, No.12, DOI:10.1109/TGRS.2020.3032427. • He, J., Yuan, Q., Li, J., Zhang, L., 2022, PoNet: A universal physical optimization-based spectral super-resolution network for arbitrary multispectral images, *Information Fusion, Vol.80,* DOI:10.1016/j.inffus.2021.10.016. • Hu, X., Wang, X., Zhong, Y., Zhang, L., 2022, S3ANet: Spectral-spatial-scale attention network for end-to-end precise crop classification based on UAV-borne H2 imagery，*ISPRS Journal of Photogrammetry and Remote Sensing, Vol.183, PP.147-163, DOI: 10.1016/j.isprsjprs.2021.10.014.* • Shi, Q., Tang, X., Yang, T., Liu, R., Zhang, L., 2022, Hyperspectral Image Denoising Using a 3-D Attention Denoising Network, IEEE Trans. on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2020.3045273. • Yang, J., Wu, C., Du, B., Zhang, L., 2022, Enhanced Multiscale Feature Fusion Network for HSI Classification, *IEEE Trans. on Geoscience and Remote Sensing, Vol.59, No.12,* DOI: 10.1109/TGRS.2020.3046757. • Ding, J., Xue, N., Xia, G.,,Zhang, L., 2021, Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges，*IEEE Trans. on Pattern Analysis and Machine Intelligence, 44 (11) , pp.7778-7796.* • Xu, Y., Du, B., Zhang, L., 2021, Self-Attention Context Network: Addressing the Threat of Adversarial Attacks for Hyperspectral Image Classification，*IEEE Trans. on Image Processing, VOL. 30, PP.8671-8685.* • Shen, H., Zhang, L., 2021, A Locally Weighted Neural Network Constrained by Global Training for Remote Sensing Estimation of PM2.5, *IEEE Trans. on Geoscience and Remote Sensing,* *VOL. 60, PP.1-13.* • Zhang, H., Chen, H., Yang, G., Zhang, L., 2021, LR-Net: Low-Rank Spatial-Spectral Network for Hyperspectral Image Denoising, *IEEE Trans. on Image Processing,* *VOL. 30, PP.8743-8758.* • Zheng, Z., Zhong, Y., Wang, J., Ma, A., Zhang, L., 2021, Building damage assessment for rapid disaster response with a deep object-based semantic change detection framework: From natural disasters to man-made disasters, *Remote Sensing of Environment, Vol.265, 112636.* • Zhu, D., Du, B., Zhang, L., 2021, Two-Stream Convolutional Networks for Hyperspectral Target Detection, *IEEE Trans. on Geoscience and Remote Sensing, VOL. 59, NO. 8, PP.6907-6921.* • Guo, H., Shi, Q., Marinoni, A., Du, B., Zhang, L., 2021, Deep building footprint update network: A semi-supervised method for updating existing building footprint from bi-temporal remote sensing images, *Remote Sensing of Environment, Vol.264, 112589.* • Chu, D., Shen, H., Guan, X., Chen, J., Li, X., Li, J., Zhang, L., 2021, Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion, *Remote Sensing of Environment, Vol.264, 112632.* • Ma, A., Chen, D., Zhong, Y., Zheng, S., Zhang, L., 2021, National-scale greenhouse mapping for high spatial resolution remote sensing imagery using a dense object dual-task deep learning framework: A case study of China, *ISPRS Journal of Photogrammetry and Remote Sensing，Volume 181, Pages 279-294. • Zhang, Q，Yuan, Q, Li, Z., Sun, F., Zhang, L., 2021, Combined deep prior with low-rank tensor SVD for thick cloud removal in multitemporal images, ISPRS Journal of Photogrammetry and Remote Sensing, Vol.177, PP.161-173.* • Wang, Y., Yuan, Q., Li, T., Tan, S., Zhang, L., 2021, Full-coverage spatiotemporal mapping of ambient PM2.5 and PM10 over China from Sentinel-5P and assimilated datasets: Considering the precursors and chemical compositions, *Science of the Total Environment, 793, 148535.* • Hong, D., He, W, Yokoya, N., Yao, J., Gao, L., Zhang, L., Chanussot, J., Zhu, X., 2021, Interpretable Hyperspectral Artificial Intelligence: When nonconvex modeling meets hyperspectral remote sensing, *IEEE Geoscience and Remote Sensing Magazine, No.2, PP.52-57. • Wang, Y., Yuan, Q., Zhu, L., Zhang, L., 2021, Estimating daily full-coverage near surface O3, CO, and NO2 concentrations at a high spatial resolution over China based on S5P-TROPOMI and GEOS-FP, ISPRS Journal of Photogrammetry and Remote Sensing, Vol.175, PP.311-325.* • Lu, X., Zhong, Y., Zheng, Z, Zhang, L., 2021, GAMSNet: Globally aware road detection network with multi-scale residual learning, *ISPRS Journal of Photogrammetry and Remote Sensing, Vol.175, PP.340-352.* • Yang, Q., Wang, B., Yuan, Q., Zhang, L., 2021, Global air quality change during COVID-19: a synthetic analysis of satellite, reanalysis and ground station data, *ENVIRONMENTAL RESEARCH LETTERS, Vol.16, No.7, 074052.* • Zhu, Q., Zhang, Y., Zhong, Y., Wang, L., Guan, Q., Zhang, L., Li, D., 2021, A Global Context-aware and Batch-independent Network for road extraction from VHR satellite imagery, *ISPRS Journal of Photogrammetry and Remote Sensing, Vol.175, PP.353-365. • Zhang, Q，Yuan, Q, Li, J., Wang, Y., Sun, F., Zhang, L., 2021, Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013-2019, Earth System Science Data* (ESSD), 13，1385-1401. • Wang, X., Zhong, Y., Zhang, L., 2021, A self-supervised denoising network for satellite-airborne-ground hyperspectral imagery, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, PP.1-16.* • Zhong, Y., Zhang, L., 2021, Multi-Objective Sine Cosine Algorithm for Remote Sensing Image Spatial-Spectral Clustering, *IEEE Trans. on Cybernetics,* • Zhao, S., Yuan, Q., Liu, X., Zhang, L., 2021, A Fast and Effective Irregular Stripe Removal Method for Moon Mineralogy Mapper (M3), *IEEE Trans. on Geoscience and Remote Sensing,* *Vol.60, PP.1-19.* • Zhu, S., Du, B., Zhang, L., 2022, Attention-based Multi-scale Residual Adaptation Network for Cross-Scene Classification,*IEEE Trans. on Geoscience and Remote Sensing, Vol.60, PP.1-15.* • Wang, S., Wang, X., Zhong, Y., Zhang, L., 2022, Auto-AD: Autonomous Hyperspectral Anomaly Detection Network Based on Fully Convolutional Autoencoder,*IEEE Trans. on Geoscience and Remote Sensing, Vol.60, PP.1-14.* • Wang, D., Du, B., Zhang, L., 2021, Fully Contextual Network for Hyperspectral Scene Parsing, *IEEE Trans. on Geoscience and Remote Sensing,* *Vol.60, PP.1-16.* • Zhang, L., 2021, SPNet: Spectral Patching End-to-End Classification Network for UAV-Borne Hyperspectral with High Spatial Resolution (H2) Imagery, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, PP.1-17.* • Yang, J., Wu, C., Du, B., Zhang, L., 2021, Enhancing Multi-scale Feature Fusion Network for HSI Classification, *IEEE Trans. on Geoscience and Remote Sensing,* *Vol.59, No. 12, PP.10328-10347.* • Zhang, H., Cai, J., He, W., Shen, H., Zhang, L., 2022, Double Low-Rank Matrix Decomposition for Hyperspectral Image Denoising and Destriping, *IEEE Trans. on Geoscience and Remote Sensing, Vol.60, PP.1-19.* • Wang, B., Yuan, Yang, Q., Zhu, L., Li, T., Zhang, L., 2021, Estimate hourly PM2.5 concentrations from Himawari-8 TOA reflectance directly using geo-intelligent long short-term memory network, *Environmental Pollution, Volume 271, PP.1-12.* • Shi, Q., Liu, R., Zhang, L., 2020, Hyperspectral Image Denoising Using a 3D Attention Denoising Network, IEEE Trans. on Geoscience and Remote Sensing, Vol.59, No. 12, PP.10348-10363. • Zheng, S., Ma, A., Zhang, L., Zhong, Y., 2021, Deep multisensor learning for missing-modality all-weather mapping, ISPRS Journal of Photogrammetry and Remote Sensing, Vol.174, PP.254-264. • Ma, A., Zhong, Y., Wang, J., Zhang, L., 2021, SceneNet: Remote sensing scene classification deep learning network using multi-objective neural evolution architecture search, ISPRS Journal of Photogrammetry and Remote Sensing, Vol.172, PP.171-188. • Zhang, H., Zhang, L., 2020, A Local-Global Dual-Stream Network for Building Extraction from Very High Resolution Remote Sensing Images, IEEE Trans. on Neural Networks and Learning Systems，Vol.33, No. 3, PP.1269-1283. • He, J., Li, J., Yuan, Q., Shen, H., Zhang, L., 2020, Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution, IEEE Trans. on Neural Networks and Learning Systems，DOI: 10.1109/TNNLS.2021.3056181. • Xu, H., Zhang, H., Zhang, L., 2021, A Superpixel Guided Sample Selection Neural Network for Handling Noisy Labels in Hyperspectral Image Classification, IEEE Trans. on Geoscience and Remote Sensing, Vol.59, No. 11, PP.9486-9503. • Zhai, H., Zhang, H., Li, P., Zhang, L., 2020, Hyperspectral Image Clustering: Current Achievements and Future Lines, IEEE Geoscience and Remote Sensing Magazine, Vol.9, No. 4, PP.35-67. • Shi, L., Yang, L., Zhao, L., Li, P., Yang, J., Zhang, L., 2020, NESZ Estimation and Calibration for Gaofen-3 Polarimetric Products by the Minimum Noise Envelope Estimator, IEEE Trans. on Geoscience and Remote Sensing, VOL.59, NO.9, PP.7517-7534. • Zhong, Y., Shi, S., Zhao, J., Lv, P., Zhang, L., 2020, Land-Use/Land-Cover Change Detection Based on Class-Prior Object-Oriented Conditional Random Field Framework for High Spatial 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(Invited paper)* • Huang , X., Zhang , L., 2009 , A Comparative Study of Spatial Approaches for Urban Mapping using hyperspectral ROSIS images over Pavia City, northern of Italy, *Int.J.Remote Sensing* , 30, No. 12 , PP.3205 – 3221. • Huang , X., Zhang , L., 2009 , Road centreline extraction from high resolution imagery based on multiscale structural features and support vector machines , *Int.J.Remote Sensing, 30, No.8, PP.1977-1987.* • Huang, X., Zhang , L., Wang, L. , 2009 , Evaluation of Morphological Texture Features for Forest Species Discrimination using IKONOS Multispectral Imagery, *IEEE Geoscience and Remote Sensing Letters, Vol.6, No.3 , PP. 393 –397* . • Shen, H., Zhang, L., 2009, A MAP-Based Algorithm for Destriping and Inpainting of Remotely Sensed Images , *IEEE Trans. on Geoscience and Remote Sensing, Vol. 47, No. 5 , PP.1492 –1502.* • Shen, H., Ng, M. K., Li, P., Zhang, L., 2009, Super-resolution Reconstruction Algorithm to MODIS Remote Sensing Images, *The Computer Journal, Vol.52, No.1 , PP. 90 –100* . • Huang , X., Zhang , L., 2008 , An Adaptive Mean Shift Analysis Approach for Object Extraction and Classification from Urban Hyperspectral Imagery , *IEEE Trans. on Geoscience and Remote Sensing* , *Vol.46, No.12, 4173-4185.* • Zhang , L., Wu, K., Zhong , Y., Li, P. , 2008, A new sub-pixel mapping algorithm based on a BP neural network with an observation model, *Neurocomputing, Vol.71 , N.10-12, PP.2046-2054.* • Huang , X., Zhang , L., Li, P. , 2008 , A multiscale feature fusion approach for classification of very high resolution satellite imagery, *Int.J.Remote Sensing,29, No. 20 ,PP. 5923 – 5941.* • Huang , X., Zhang , L., Li, P. , 2008 , Classification of very high spatial resolution imagery based on the fusion of edge and multispectral information, *Photogrammetric Engineering and Remote Sensing , Vol.74, No.12 , PP. 1585 –1596.* • Zhang , L., Zhao , Y., Huang, B. , Li, P. , 2008 , Texture Feature Fusion with Neighborhood Oscillating Tabu Search for High Resolution Image, *Photogrammetric Engineering and Remote Sensing,* *Vol.74, No.3* , *PP.323-332* . • Huang , X., Zhang , L., Li, P. , 2007 , An adaptive multiscale information fusion approach for feature extraction and classification of very high resolution satellite imagery, *IEEE Geoscience and Remote Sensing Letters, Vol.4, No.4, PP.654-658.* • Zhong , Y., Zhang , L., Gong, J., Li, P. , 2007, A Supervised Artificial Immune Classifier for Remote Sensing Imagery, *IEEE Trans. On Geoscience and Remote Sensing, Vol.45, No.12, PP.3957-3966.* • Wang , Y., Zhang , L., Li, P. , 2007, A Scale-Based Forward-and-Backward Diffusion Algorithm for Image Enhancement and Noise Reduction, *IEEE Trans. on Image Processing, Vol.16, No.7, PP.1854-1864* . • Ng, M. K., Shen, H., Lam , E., Zhang , L., 2007 , A Total Variation Based Super-Resolution Reconstruction Algorithm for Digital Video , *EURASIP Journal On Advances In Signal Processing: Art. No. 74585 2007.* • Niu, R., Zhang, L., Shao, Z., Chen, Q., 2007, Web-based Geological Hazard Monitoring in Three Gorges, *Photogrammetric Engineering and Remote Sensing, Vol.73, No.6* , *PP.707 - 719* . • Huang , X., Zhang , L., Li, P. , 2007 , Classification and Extraction of Spatial Features in Urban Areas using High Resolution Multispectral Imagery , *IEEE Geoscience and Remote Sensing Letters, Vol.4, No.2 , PP.260 - 264* . • Zhao , Y., Zhang , L., Li, P. , 2007 , Classification of High Spatial Resolution Imagery Using Improved General Markov Random Field – Based Texture Features, *IEEE Trans. On Geoscience and Remote Sensing, Vol.45, No.5, PP.1458 -1468* . • Zhang, L., Wu, B., Huang, B., Li, P., 2007, Nonlinear Estimation of Subpixel Proportion Via Kernel Least Square Regression, *Int.J.Remote Sensing, 28, No.18, PP. 4157 – 4172.* • Zhang, L., Zhang, L., Yan, L., Yang, S., Fujiwara, N., Murumatsu, K., Daigo, M., 2007 , Hyperspectral data transformation and vegetation index performance based on the universal pattern decomposition method , *Journal of Imaging Science and Technology,* *Vol.51, No.2* *PP.141-147* . • Zhang , L., Zhong , Y. , Huang, B. , Li, P. , 2007, Dimensionality Reduction Based on Clonal Selection for Hyperspectral Imagery, *IEEE Trans. On Geoscience and Remote Sensing, Vol.45, No.12, PP.4172-4185.* • Zhang , L., Zhong , Y., Huang, B. , Li, P. , 2007, A Resource Limited Artificial Immune Algorithm for Supervised Classification of Multi/Hyper-Spectral Remote Sensing Image, *Int.J.Remote Sensing* , *Vol. 28, No.7, PP.1665 - 1686* . • Shen, H., Zhang , L., Huang, B. , Li, P. , 2007, A MAP Approach for Joint Motion Estimation, Segmentation and Super Resolution, *IEEE Trans. on Image Processing, Vol.16, No.2,PP.479-490.* • Zhang, L., Furumi, S., Murumatsu, K., Fujiwara, N., Daigo, M., and Zhang, L., 2007, A New Vegetation Index Based on the Universal Pattern Decomposition Method, *Int.J.Remote Sensing, 28(1):107-124.* • Zhang, L., Fujiwara, N., Furumi, S., Muramatsu, K., Daigo, M., and Zhang, L, 2007, Assessment of the universal pattern decomposition method using MODIS and ETM+ data, *Int.J.Remote Sensing, 28(1):125-142.* • Zhang, L., Furumi, S., Murumatsu, K., Fujiwara, N., Daigo, M., and Zhang, L., 2006, Sensor-independent analysis method for hyper-multi spectral data based on the pattern decomposition method, *Int.J.Remote Sensing,* *27(21): 4899-4910.* • Zhang , L., Huang , X., Huang, B. , Li, P. , 2006 , A pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery , *IEEE Trans. on Geoscience and Remote Sensing, Vol.44, No.10, PP. 2950–2961* . • Wu, B., Zhang, L., Li, P., 2006, Nonlinear Estimation of Hyperspectral Mixture Pixel Proportion Based on Kernel Orthogonal Subspace Projection, *Lecture Notes In Computer Science 3971: 1070-1075 Part 1: Advanced In Neural Networks* . • Zhong , Y., Zhang , L., Huang, B. , Li, P. , 2006, An Unsupervised Artificial Immune Classifier for Multi/hyper-spectral Remote Sensing Image, *IEEE Trans. on Geoscience and Remote Sensing, Vol.44, No.2, PP. 420–431* . • Zhang, L., Li, D., 1999, Artificial neural network application in spectral recognition, *Spectroscopy and Spectral Analysis 19 (2): 158-160* . • Zhang, L., Li, D., Tong, Q., Zheng, L., 1998, A study of the spectral mixture model of soil and vegetation in Poyang lake area, China, *Int.J.Remote Sensing, Vol.19, PP. 2077-2084. 出书 Book* • Zhang , L., Zhong , Y., 2009, Analysis of Hyperspectral Remote Sensing images, *Geospatial Technology for Earth Observation, Springer.* • 沈焕锋、程青、李星华、曾超、张良培， 2018，遥感数据质量改善之信息重建, *科学出版社。 • 沈焕锋、袁强强、李杰、岳林慰、张良培， 2018，遥感数据质量改善之信息复原, 科学出版社。 • 沈焕锋、李慧芳、李星华、张良培， 2018，遥感数据质量改善之信息校正, 科学出版社。 • 张良培、杜博、张乐飞，2012，高光谱遥感图像处理, 科学出版社。 • 张良培、沈焕峰、张洪艳、袁强强，2012，图像超分辨率重建，科学出版社。 • 张良培、张立福, 2011 ,高光谱遥感, 测绘出版社* 。 • 张良培、张立福, 2005 ,高光谱遥感, *武汉大学出版社* 。专利 Patents • 一种自适应变分遥感影像融合方法, 201010227696.3. L. Zhang, et al., 2010, An Adaptive Variation Method of Remote Sensing Image Fusion. • 一种推扫式卫星影像 CCD 相对辐射校正方法 200410060986.8 • 一种遥感影像的人工免疫监督分类方法 200610019506.2 L. Zhang, et al., 2006, An Artificial Immune Surveillance Method for Remote Sensing Image Classification. • 一种遥感影像的人工免疫特征选择方法 200610019507.7 L. Zhang, et al., 2006, An Artificial Immune Feature Selection Method for Remote Sensing Images. • 一种遥感影像的人工免疫非监督分类方法 200610019508.1 • 一种可调节的光谱和空间特征混合分类方法 200610124494.X • L. Zhang, et al., 2013, Hyperspectral Imagery Restoration With Band Clustering and Sparse Representation. • L. Zhang, et al., 2013, A Piece-Wise Approach to Removing the Stripes of Remote Sensing Image. • L. Zhang, et al., 2013, Thick Cloud Removal for Remotely Sensed Images Using Multi-Temporal Data. • L. Zhang, et al., 2013, A Restoration Method Using Multi-temporal Weighted Regression for Remote Sensing Imagery. • L. Zhang, et al., 2011, A DNA Based Spectral Matching Method for Hyperspectral Remote Sensing Image Classification. • L. Zhang, et al., 2011, Hyperspectral Remote Sensing Image Sub-Pixel Mapping Based on Clonal Selection. • L. Zhang, et al., 2010, A Hyperspectral Remote Sensing Anomaly Detection Method. • L. Zhang, et al., 2010, Hyperspectral Imaging Target Detection Based on Selective Endmembers. • L. Zhang, et al., 2007, A Hybrid Spectral and Spatial Classification Method for Remote Sensing Images. • L. Zhang, et al., 2007, Shape of Spatial Feature Extraction and Classification for Remote Sensing Images.
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