MEGACOSM – DETECTION AND CLASSIFICATION OF ASTRONOMICAL OBJECTS

Abstract

The concept of existence started with the bigbang theory, which was a phenomenon where multiple objects collided to create multiple other things. This creation is said to be increasing at the rate of the cosmic acceleration due to which multiple new objects came into existence called as the astronomical objects. Space object (SO) detection, classification, and characterization are significant challenges in many research fields. In recent years, deep learning and other forms of artificial intelligence (AI) have drawn the attention of many astronomers and academics. Megacosm is project that is used for the classification and the identification of those newly created celestial objects. It works on the process of manually training the model with the data annotation techniques and the dataset is enhanced using the data augmentation technique. It uses YOLO as the core algorithm and also deep learning concepts like CNN (Convolution Neural Network) to predict results. It gives the output as a bounding box around the detected object along with the accuracy of that prediction.