Enhancing Process Image Analysis with Adaptive Thresholding and Deep Learning Techniques

This paper presents a deep learning model specifically designed to effectively classify display Mura images. The model leverages advanced deep learning techniques and computer vision methods to identify and categorize various types of Mura based on their unique digital signatures and visual patterns. It aims to provide fast and accurate classification results, enabling real-time processing of large-scale image data. The model is expected to significantly enhance content management and user experience with display Mura, and it can be innovatively applied across various fields of image classification.