METHODS AND SYSTEMS FOR FAULT TOLERANT TRAINING FOR REAL TIME DEFECT DETECTION IN MANUFACTURING

Embodiments of the present disclosure discuss a system [100] and a method [200] for refining training images for object detection. Conventional systems provide inaccurate predictions of defects because of erroneous labeling of defects in training images. Further, existing systems focus on improving the algorithms used for object detection. Embodiments of the present disclosure address these problems by using supervised learning techniques and refining the training data provided to train the algorithms. The system [100] refines the training images using predictions of a first model and providing the predictions for human review, and subsequently uses the refined training images to create a second model that can be used in a production environment of an enterprise for object detection.