Aircraft-Type Classification Using Deep Learning Algorithms

In the field of artificial intelligence (AI), deep learning (DL) has become an essential methodology with many uses, particularly in the aviation sector. The efficiency and effectiveness of tasks connected to aircraft recognition and classification are considerably improved by DL. The goal of this study is to examine and deal with problems related to efficiency and accuracy in DL models for identifying and classifying aircrafts. In this article, we suggest a solution that utilizes a customized convolutional neural network (CNN) model that our team has created and assess its performance in comparison to other deep learning (DL) models like VGG16 and ResNet50. Accuracy, recall, precision, and f1-score are among the metrics used for evaluation. The outcomes of this study demonstrate significant gains and offer insightful information for future endeavors in the aviation field.