Sentinel-2 New Anomalies AI4QC

This dataset was used in the AI4QC project (Artificial Intelligence for Quality Control), in the context of the detection of new anomalies through unsupervised learning (unlabeled data). It consists of 6452 Sentinel-2 images (true color images in jpg format). The dataset was divided into training and testing folders (80% training and 20% testing). Two criterias were considered for the train/test split: seasonality and geographic location. 

An additional folder, "S2_additional_data" contains 61 more products which were flagged as anomalous by the MPC. This data is not included in the train/test folders but can be used if one wishes to increase the amount of S2 products.

本数据集应用于AI4QC（质量控制人工智能，Artificial Intelligence for Quality Control）项目，旨在通过无监督学习（无标注数据）检测新型异常样本。该数据集包含6452张Sentinel-2（哨兵二号）卫星真彩色图像，格式为JPEG。数据集被划分为训练集文件夹与测试集文件夹，比例为80%训练集、20%测试集。训练/测试集的划分遵循两项标准：季节性与地理位置。另有一个名为"S2_additional_data"的额外文件夹，内含61份被MPC标记为异常的产品数据。该部分数据未纳入训练集与测试集文件夹，若用户希望扩充Sentinel-2产品的样本量，可使用该数据集。