A Gan Based X-Ray Model for Detecting Objects using Convolution Neural Networks
Baggage screening is one of the most important tasks when it comes to public gatherings and areas. Numerous railway stations and airports have the process of screening the baggage of the passengers to find out if any abnormal things are present. Other areas such as temples, shopping malls also have these systems to ensure the security of the gathering. It becomes very difficult for the screening when there is a large crowd, and changes occur where most of the baggage are not properly screened or consumes more time. In this paper, we have proposed a GAN based X-Ray system for scanning the baggage in a very efficient time. The images are scanned by extracting the items using a data augmentation method using GAN based approach. various parameters are being evaluated for the model and are in turn verified with the convolution Neural Network to check its validity. The performance of the model is more accurate as the model uses CNN for training and testing purposes.