A Survey on Image Processing and its Algorithms

Abstract

This paper reviews the rapid advancements in deep learning techniques for image processing. From the classification and clustering of multi-structured data to the development of innovative algorithms, deep learning has transformed traditional approaches to handling complex data challenges. The survey examines current deep learning methods, including CNNs, YOLO, and transfer learning, and their applications in areas such as healthcare, facial recognition, and autonomous vehicles. We also explore recent innovations, such as facial diagnosis using deep learning, adaptable image processing pipelines, and smart attendance monitoring systems. By synthesizing these findings, this paper highlights the progress and potential of deep learning in image processing.