相关数据集
REOBench
REOBench是一个用于评估地球观测基础模型鲁棒性的综合基准，涵盖了基于掩码图像建模、对比学习和视觉语言预训练范式训练的广泛模型。数据集专注于高分辨率光学遥感图像，广泛应用于城市规划、灾害响应等关键领域。该基准包括12种图像退化类型，包括基于外观和几何的扰动。数据集的构建过程包括系统地评估了众多模型，以揭示当前地球观测基础模型在实际世界扰动下的脆弱性，并为开发更鲁棒和可靠的模型提供了可操作的见解
arXiv2025-05-22 更新650
Building detection with multi-view colour infrared imagery.
This paper presents an automatic building detection approach exploiting colour infrared (CIR) imagery. A Digital Surface Model (DSM) is first extracted by photogrammetry with a proprietary development
DataCite Commons2021-01-03 更新120
Amazon Rainforest dataset for semantic segmentation V2
This database contains images used for training a fully convolutional neural network for the semantic segmentation of forested areas in images from the Sentinel-2 Level 2A Satellite. The images refer
Mendeley Data2024-03-27 更新170
Superresolution Reconstruction of Severely Undersampled Point-spread Functions Using Point-source Stacking and Deconvolution
Point-spread function (PSF) estimation in spatially undersampled images is challenging because large pixels average fine-scale spatial information. This is problematic when fine-resolution details are
DataCite Commons2023-09-15 更新100
