SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets
收藏DataCite Commons2024-12-16 更新2025-04-16 收录
下载链接：
https://service.tib.eu/ldmservice/dataset/96cee4a9-6137-4341-8952-9bd144bb7d61
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资源简介：
Geospatial datasets are diverse, naturally spatiotemporal, and inherently multimodal (composed of two or more distinct signal types or modalities) e.g., satellite/aerial imagery (RGB, multispectral), road network graphs, vector geometry, sensor data (LiDAR-based point cloud, IMU data, GPS-based mobility data), active sensing imagery (SAR, Sonar, Radar).
提供机构：
TIB
创建时间：
2024-12-16
