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Few-shot earth surface anomaly detection via large vision-language models
- “In recent years, sudden surface anomalies have occurred frequently. To address the problem of insufficient annotated samples in the early stages of sudden anomalies, a lightweight small sample surface anomaly detection method based on a visual language pre training model is proposed, providing a solution to the problem of remote sensing emergency monitoring.”
- Pages: 1-18(2026)
DOI:10.11834/jrs.20266048
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ZHU Xiufang 北京师范大学 遥感与数字地球全国重点实验室;北京师范大学 环境演变与自然灾害教育部重点实验室;北京师范大学 地理科学学部遥感科学与工程研究院
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SONG Junying 北京师范大学 遥感与数字地球全国重点实验室;北京师范大学 环境演变与自然灾害教育部重点实验室
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Related Institution
State Key Laboratory of Remote Sensing and Digital Earth, Beijing Normal University
Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University
Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University
State Key Laboratory of Remote Sensing and Digital Earth/Faculty of Geographical Science, Beijing Normal University
College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing


