Anomaly Detection dataset for the fuselage of an aircraft

If you use the dataset, please cite: <em>Siddhant Shete, Dennis Mronga</em> <strong>"Adaptive Online Anomaly Detection using Transfer Learning"</strong> About the dataset: The dataset is basically used for anomaly detection in the fuselage of an aircraft manufacturing company. We captured the data on the mockup of the fuselage with several iterations at different distances away from the mockup. The dataset is basically the scans of mockup from top to bottom with and without anomalies. The dataset has been segregated into two panels. Contents of <em><strong> AircraftFuselageMockupDataset.zip </strong></em> Nomal_panel1 Nomal_panel2 Anomaly_panel1 Anomaly_panel2 Every folder has data at 3 distances 15cm, 25cm, 35cm. <em>This dataset is provided by the Robotics Innivation Center, DFKI GmbH.</em> <em>The grant was provided by Federal Ministry for Economic Affairs and Climate Action </em> <em>Grant number: 20W1922F</em>若使用本数据集，请引用：<em>Siddhant Shete、Dennis Mronga</em> 发表的<strong>《基于迁移学习的自适应在线异常检测》</strong> 数据集说明：本数据集主要用于某飞机制造企业机身的异常检测任务。我们针对机身样机，在距样机不同距离下开展了多轮数据采集。本数据集本质为机身样机自上而下的扫描数据，涵盖存在异常与无异常两类场景。数据集被划分为两个分组面板。 <em><strong>AircraftFuselageMockupDataset.zip</strong></em> 包含以下内容： 正常面板1、正常面板2、异常面板1、异常面板2 每个文件夹均包含15cm、25cm、35cm三个不同采集距离下的数据。 本数据集由DFKI GmbH机器人创新中心（Robotics Innivation Center）提供。 本研究受联邦经济事务与气候行动部（Federal Ministry for Economic Affairs and Climate Action）资助，资助编号：20W1922F。