周勇胜，教授，硕士生导师

项目名称

项目来源

基于泛在稳定目标特性转换的SAR辐射交叉定标方法研究

国家自然科学基金面上项目

岛礁和海上构筑物多尺度信息综合提取技术

国家重点研发计划课题

新体制星载SAR系统定标方法与高精度误差补偿技术

国家重点研发计划子课题

微波凝视关联成像目标特性建模与检测识别新方法研究

国家自然科学基金面上项目

无人机载极化干涉SAR森林高度反演方法研究

国家自然科学基金青年项目

复杂自然场景下微波凝视关联图像质量评价技术

国家863计划子课题

研究方向

论文专利

SAR定标

[1]     Y. Zhou Y, P. Chen, Q. Yin, E.   Chen, L. Ferro-Famil, F. Zhang. Polarimetric SAR Cross-Calibration Method   based on Stable Distributed Targets [J], Geo-spatial Information Science, 2024.

[2]     Y. Zhou, L. Zhuang, J. Duan, F. Zhang,   W. Hong. Synthetic Aperture Radar Radiometric Cross Calibration Based on   Distributed Targets [J]. IEEE Journal of Selected Topics in Applied Earth   Observations and Remote Sensing, 2022, 15: 9599–9612.

[3]     Y. Zhou, C. Li, L. Tang, L. Ma, Q.   Wang, Q. Liu. A Permanent Bar Pattern Distributed Target for Microwave Image   Resolution Analysis [J]. IEEE Geoscience and Remote Sensing Letters, 2017,   14(2): 164–168.

[4]     周勇胜、应倩、张帆、马飞、尹嫱，基于海上风电场的SAR交叉辐射定标方法，202311466740.X，受理

[5]     周勇胜、陈佩芸、张帆、尹嫱、马飞，一种极化合成孔径雷达交叉定标方法，202310449169.4，受理

[6]     周勇胜、庄丽、张帆、尹嫱、孙晓坤、马飞、项德良，一种SAR交叉定标参考目标选择方法，202110964448.5，授权

[7]     周勇胜、庄丽、张帆、尹嫱、孙晓坤、马飞、项德良，一种合成孔径雷达交叉定标方法，202110692072.7，授权

目标检测识别

[1]    Y. Zhou, H. Liu, F. Ma, Z. Pan,   F. Zhang. A Sidelobe-Aware Small Ship Detection Network for Synthetic   Aperture Radar Imagery [J], IEEE Transactions on Geoscience and Remote   Sensing, 2023, 61: 1-16.

[2]    Y. Zhou, F. Zhang, Q. Yin, F. Ma   and F. Zhang. Inshore Dense Ship Detection in SAR Images Based on Edge   Semantic Decoupling and Transformer [J], IEEE Journal of Selected Topics in Applied Earth Observations and   Remote Sensing, 2023, 16: 4882-4890.

[3]    Y. Zhou, F. Zhang, F. Ma, D. Xiang,   F. Zhang. Small Vessel Detection Based on Adaptive Dual-Polarimetric Feature   Fusion and Sea-Land Segmentation in SAR Images [J]. IEEE Journal of Selected   Topics in Applied Earth Observations and Remote Sensing, 2022, 15: 2519–2534.

[4]    Y. Zhou, S. Zhang, X. Sun, F. Ma,   F. Zhang. SAR Target Incremental Recognition Based on Hybrid Loss Function   and Class-Bias Correction [J]. Applied Sciences, 2022, 12(3).

[5]    Y. Liu, G. Yan, F. Ma, Y. Zhou, F.   Zhang. SAR Ship Detection Based on Explainable Evidence Learning under   Intra-class Imbalance [J]. IEEE Transactions   on Geoscience and Remote Sensing, 2024.

[6]    F. Ma, X. Sun, F. Zhang, Y. Zhou,   H.-C. Li. What Catch Your Attention in SAR Images: Saliency Detection Based   on Soft-Superpixel Lacunarity Cue [J]. IEEE Transactions on Geoscience and   Remote Sensing, 2023, 61: 1–17.

[7]    周勇胜、张飞翔、张帆、马飞、尹嫱、项德良，基于增强型特征金字塔的双极化SAR小型船只检测方法，202110514236.7，授权

图像分割

[1]    Y. Zhou, K. Yang K, F. Ma, W. Hu,   F. Zhang. Water–Land Segmentation via Structure-Aware CNN–Transformer Network on Large-Scale SAR Data [J]. IEEE Sensors   Journal, 2023, 23(2): 1408–1422.

[2]    F. Ma, F. Zhang, Q. Yin, D. Xiang,   Y. Zhou. Fast SAR Image Segmentation with Deep Task-Specific Superpixel   Sampling and Soft Graph Convolution [J]. IEEE Transactions on Geoscience and   Remote Sensing, 2022, 60: 1–16.

[3]    F. Ma, F. Zhang, D. Xiang, Q.   Yin and Y. Zhou. Fast Task-Specific Region Merging for SAR Image Segmentation   [J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1–16.

[4]    Z. Zhang, S. Tan, Y. Zhou.   CloudformerV3: Multi-Scale Adapter and Multi-Level Large Window Attention for   Cloud Detection [J]. Applied   Sciences, 13(23).

[5]    Z. Zhang, Z. Xu, C. Liu, Q. Tian,   Y. Zhou. Cloudformer V2: Set Prior Prediction and Binary Mask Weighted   Network for Cloud Detection [J]. Mathematics, 2022, 10(15).

[6]    Z. Zhang, C. Miao, C. Liu, Q. Tian,   Y. Zhou. HA-RoadFormer: Hybrid Attention Transformer with Multi-Branch for Large-Scale   High-Resolution Dense Road Segmentation [J]. Mathematics, 2022, 10(11).

[7]    张帆、倪军、尹嫱、周勇胜、洪文，基于深度递归网络下小样本极化合成孔径雷达图像分类方法，201911301348.3，受理

地物分类

[1]    Y. Zhou, P. Chen, N. Liu, Q.   Yin, F. Zhang. Graph-Embedding Balanced Transfer Subspace Learning for   Hyperspectral Cross-Scene Classification [J]. IEEE Journal of Selected Topics   in Applied Earth Observations and Remote Sensing, 2022, 15: 2944–2955.

[2]    Y. Da, Z. Ji, Y. Zhou. Building   Damage Assessment Based on Siamese Hierarchical Transformer Framework [J].   Mathematics, 2022, 10(11).

[3]    Y. Wang, J. Cheng, Y. Zhou, F.   Zhang, Q. Yin. A Multichannel Fusion Convolutional Neural Network Based on   Scattering Mechanism for PolSAR Image Classification [J]. IEEE Geoscience and   Remote Sensing Letters, 2022, 19: 1–5.

[4]    Q. Yin, J. Li, Y. Zhou, D. Xiang,   F. Zhang. Adaptive Weighted Learning for Vegetation Contribution in Soil   Moisture Inversion Using PolSAR Data [J]. International Journal of Remote   Sensing, 2022, 43(9): 3190–3215.

[5]    周勇胜、王亚楠、程建达、张帆、尹嫱、项德良、马飞、洪文，一种基于散射机制多通道扩张卷积神经网络的极化SAR地物分类方法，202110365566.4，授权

[6]    尹嫱、黄译、张帆、周勇胜，一种基于散射机制用于简缩极化SAR的交互CNN分分类方法，202111540134.9，受理

[7]    尹嫱、罗莹、马飞、周勇胜、张帆、洪文，一种基于双极化SAR特征的水体悬浮物空间分布监测方法，202310412453.4，受理