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. If you use our datasets in your academic research, please cite our articles "A Semi-Supervised Aircraft Fuselage Defect Detection Network with Dynamic Attention and Class-aware Adaptive Pseudo-Label Assignment".