Editor Profile
Dr. Yujia Chen, Ph.D.
Associate Professor
Present
Xi'an University of Architecture and Technology
Xi'an
China
Chen Yujia received her Ph.D. in Photogrammetry and Remote Sensing from the State Key Laboratory of Surveying and Mapping Remote Sensing Information Engineering at Wuhan University. She is currently an associate professor at the College of Urban Development and Modern Transportation, Xi'an University of Architecture and Technology. Her research focuses on weakly supervised intelligent interpretation of remote sensing images. She has published 15 academic papers in major domestic and international journals, including 8 as first author/corresponding author. Her research emphasizes key issues in remote sensing such as sparse sample learning, low-resolution sample learning, and robustness learning against noisy labels. She has proposed innovative solutions, contributing to reducing annotation costs and improving intelligent interpretation efficiency. Her research findings have been published in journals such as the ISPRS Journal of Photogrammetry and Remote Sensing and IEEE Transactions on Geoscience and Remote Sensing. She also serves as a reviewer for several SCI journals, including the ISPRS Journal of Photogrammetry and Remote Sensing, Science of remote sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, and The International Geoscience and Remote Sensing Symposium.
- Remote Sensing
- Artificial Intelligence
- Land Cover Classification
- Weakly Supervised Learning
- Superpixel aware credible dual-expert learning for land cover mapping using historical land cover map. ISPRS Journal of Photogrammetry and Remote Sensing, 2025 ,223, 296-316. (First author)
- A Credible Dual-CNN Expert-Guided Transformer for Remote Sensing Image Segmentation With Sparse Point Annotation. IEEE Transactions on Geoscience and Remote Sensing, 2025, 63, 1-16. (First author)
- A novel weakly supervised semantic segmentation framework to improve the resolution of land cover product. ISPRS Journal of Photogrammetry and Remote Sensing, 2023,196, 73-92. (First author)
- Knowledge evolution learning: A cost-free weakly supervised semantic segmentation framework for high-resolution land cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 2024, 207,74-91.（Corresponding author）
- Feature-Level Fusion between Gaofen-5 and Sentinel-1A Data for Tea Plantation Mapping. Forests, 2020, 11(12), 1357. (First author)
- Comparison of pixel- and object-based image analysis for tea plantation mapping using hyperspectral GF-5 and SAR data. Journal of Applied Remote Sensing,2020,14,044516. (First author)
- Evaluation of Mine Exploitation Intensity Based on Topsis and BP Neural Network: A Case Study in Fujian Province, China. 2019 IEEE International Geoscience and Remote Sensing Symposium, 6437-6440. (First author)
- 矿山地质环境评价中最佳评价尺度确定方法的研究及应用.现代地质,2020,34(03):626-634. (First author)
- Progressive fusion learning: A multimodal joint segmentation framework for building extraction from optical and SAR images[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2023, 195, 178-191. (Co-author)
- MCANet: A joint semantic segmentation framework of optical and SAR images for land use classification[J]. International Journal of Applied Earth Observation and Geoinformation, 2022, 106, 102638. (Co-author)
- Association of land urbanization and type 2 diabetes mellitus prevalence and mediation of greenness and physical activity in Chinese adults[J]. Environmental Pollution, 2023, 337, 122579. (Co-author)
- Stable Prototype-Guided Single-Temporal Supervised Learning for Change Detection and Extraction of Building[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61, 1-22. (Co-author)
- DecRecNet: A Decoupling-Reconstruction Network for Restoring the Missing Information of Optical Remote Sensing Images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023, 16, 9777-9801. (Co-author)
