地市级人口热力查询|人口分析数据集|政务信息推送数据集
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Tropicos
Tropicos是一个全球植物名称数据库,包含超过130万种植物的名称、分类信息、分布数据、图像和参考文献。该数据库由密苏里植物园维护,旨在为植物学家、生态学家和相关领域的研究人员提供全面的植物信息。
www.tropicos.org 收录
FER2013
FER2013数据集是一个广泛用于面部表情识别领域的数据集,包含28,709个训练样本和7,178个测试样本。图像属性为48x48像素,标签包括愤怒、厌恶、恐惧、快乐、悲伤、惊讶和中性。
github 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
UniProt
UniProt(Universal Protein Resource)是全球公认的蛋白质序列与功能信息权威数据库,由欧洲生物信息学研究所(EBI)、瑞士生物信息学研究所(SIB)和美国蛋白质信息资源中心(PIR)联合运营。该数据库以其广度和深度兼备的蛋白质信息资源闻名,整合了实验验证的高质量数据与大规模预测的自动注释内容,涵盖从分子序列、结构到功能的全面信息。UniProt核心包括注释详尽的UniProtKB知识库(分为人工校验的Swiss-Prot和自动生成的TrEMBL),以及支持高效序列聚类分析的UniRef和全局蛋白质序列归档的UniParc。其卓越的数据质量和多样化的检索工具,为基础研究和药物研发提供了无可替代的支持,成为生物学研究中不可或缺的资源。
www.uniprot.org 收录
CosyVoice 2
CosyVoice 2是由阿里巴巴集团开发的多语言语音合成数据集,旨在通过大规模多语言数据集训练,实现高质量的流式语音合成。数据集通过有限标量量化技术改进语音令牌的利用率,并结合预训练的大型语言模型作为骨干,支持流式和非流式合成。数据集的创建过程包括文本令牌化、监督语义语音令牌化、统一文本-语音语言模型和块感知流匹配模型等步骤。该数据集主要应用于语音合成领域,旨在解决高延迟和低自然度的问题,提供接近人类水平的语音合成质量。
arXiv 收录