Aircraft _Fuselage_DET2023: An Aircraft Fuselage Defect Detection Dataset

This dataset collects samples of different types of surface defects on aircraft fuselages to facilitate the identification and location of aircraft fuselage defects by computational vision and machine learning algorithms. The dataset consists of 5,601 images of four types of aircraft fuselage defects. The camera was used to photograph different parts of the aircraft fuselage in different lighting environments. Identifying and locating the defects of aircraft fuselage is extremely important for aircraft surface quality inspection and is a necessary link in the process of aircraft maintenance support. Consequently, this dataset serves as a valuable resource for researchers and practitioners engaged in the detection of aircraft fuselage defects.

本数据集收集了多类飞机机身表面缺陷样本，旨在依托计算机视觉（computational vision）与机器学习（machine learning）算法实现飞机机身缺陷的识别与定位。该数据集共包含5601张涵盖四类飞机机身缺陷的图像，采集过程中使用相机在不同光照环境下对飞机机身的不同部位进行拍摄。飞机机身缺陷的识别与定位，对于飞机表面质量检测至关重要，亦是飞机维修保障流程中的必要环节。因此，本数据集可为从事飞机机身缺陷检测工作的科研人员与行业从业者提供宝贵的研究资源。

搜集汇总

背景与挑战

背景概述

该数据集包含5,601张飞机机身缺陷图像，涵盖四种缺陷类型，旨在为计算机视觉和机器学习算法提供研究资源，支持飞机机身缺陷的检测和定位。数据集包含标注和未标注数据，适用于飞机表面质量检查及维护支持研究。