A STUDY ON DEEP LEARNING MODELS AND ALGORITHMS USED IN COMPUTER VISION

Abstract

One of the most interesting and popular subfields of artificial intelligence is computer vision. Without even realizing it, you have probably come across and utilized computer vision apps. Computer vision techniques are revolutionizing industries worldwide, whether it is for electronic deposit picture processing or crop quality control via image classification. The goal of computer vision is to mimic the intricate functioning of the human visual system so that a machine or computer can recognize and process various items in pictures and videos in a similar manner to a human. Computer vision algorithms are now able to process enormous amounts of visual data thanks to developments in deep learning, neural networks, artificial intelligence, and machine learning. In certain tasks, such as object detection and labeling, computer vision algorithms have outperformed humans in terms of speed and accuracy. Deep learning methods are now mostly applied to computer vision. This study investigates many applications of deep learning in computer vision