Aviation-security X-ray equipment is used to screen objects, while human screeners re-examine baggage and travelers to detect prohibited objects. Artificial Intelligence technology is applied to increase the accuracy in searching guns and knives, considered the most dangerous in X-ray images at baggage and aviation security screening. Artificial intelligence aviation security X-ray detects objects, finds them rapidly, reducing screeners’ labor, thereby providing better service to passengers. In this regard, neural networks based on machine learning have been continuously updated to develop such advanced equipment. In this study, the neural network O-Net is developed to improve object detection. O-Net is developed based on U-Net. The developed O-Net is tested for various neural networks, providing a wide range of experimental results.