“Instilling me thelove for history”: pages from a notebook on History of Civilization of the student Maria Thetis Nunes|历史教育数据集|教育史数据集
收藏Project Gutenberg
Project Gutenberg是一个提供免费电子书的数据集,包含超过60,000本免费电子书,涵盖了文学、历史、科学等多个领域。这些电子书主要以公共领域作品为主,用户可以自由下载和使用。
www.gutenberg.org 收录
Materials Project 在线材料数据库
Materials Project 是一个由伯克利加州大学和劳伦斯伯克利国家实验室于 2011 年共同发起的大型开放式在线材料数据库。这个项目的目标是利用高通量第一性原理计算,为超过百万种无机材料提供全面的性能数据、结构信息和计算模拟结果,以此加速新材料的发现和创新过程。数据库中的数据不仅包括晶体结构和能量特性,还涵盖了电子结构和热力学性质等详尽信息,为研究人员提供了丰富的材料数据资源。相关论文成果为「Commentary: The Materials Project: A materials genome approach to accelerating materials innovation」。
超神经 收录
全国 1∶200 000 数字地质图(公开版)空间数据库
As the only one of its kind, China National Digital Geological Map (Public Version at 1∶200 000 scale) Spatial Database (CNDGM-PVSD) is based on China' s former nationwide measured results of regional geological survey at 1∶200 000 scale, and is also one of the nationwide basic geosciences spatial databases jointly accomplished by multiple organizations of China. Spatially, it embraces 1 163 geological map-sheets (at scale 1: 200 000) in both formats of MapGIS and ArcGIS, covering 72% of China's whole territory with a total data volume of 90 GB. Its main sources is from 1∶200 000 regional geological survey reports, geological maps, and mineral resources maps with an original time span from mid-1950s to early 1990s. Approved by the State's related agencies, it meets all the related technical qualification requirements and standards issued by China Geological Survey in data integrity, logic consistency, location acc racy, attribution fineness, and collation precision, and is hence of excellent and reliable quality. The CNDGM-PVSD is an important component of China' s national spatial database categories, serving as a spatial digital platform for the information construction of the State's national economy, and providing informationbackbones to the national and provincial economic planning, geohazard monitoring, geological survey, mineral resources exploration as well as macro decision-making.
DataCite Commons 收录
MultiResSAR
MultiResSAR数据集是由武汉大学构建并发布的,包含超过10k对多源、多分辨率、多场景的SAR和光学遥感图像。该数据集旨在为多分辨率SAR与光学遥感图像配准研究提供基准数据,以评估和比较不同配准算法的性能。数据集涵盖了从低分辨率到高分辨率的图像,能够帮助研究者更好地理解和克服高分辨率图像配准中的挑战,如噪声抑制、三维几何信息的融合、跨视角几何变换建模以及深度学习模型的优化等。
arXiv 收录
SATIR
SATIR是由北京航空航天大学创建的大规模热红外图像分割数据集,包含超过100,000张带有像素级标注的图像。该数据集涵盖了城市、室内外、航空等多种场景,旨在通过利用Segment Anything Model (SAM) 生成的伪标签进行预训练,提高特定类别的热红外图像分割精度。数据集的创建过程涉及使用SAM模型对未标记的热红外图像进行分割,生成高质量的分割掩码,进而构建伪标签。SATIR数据集的应用领域主要集中在热红外图像的分割任务,特别是在标注困难的情况下,提供了一种有效的预训练解决方案。
arXiv 收录