Computer Vision: Advances in Image and Video Analysis

Abstract

The topic of computer vision has emerged as one that is fast developing, altering how we examine and comprehend pictures and movies. Image and video analysis has significantly advanced in recent years, opening the door for applications in a variety of industries including healthcare, robotics, surveillance, and autonomous systems. An overview of current developments in computer vision methods, algorithms, and techniques used in image and video analysis is given in this abstract. In conclusion, there have been tremendous improvements in image and video analysis in the field of computer vision. Recurrent neural networks (RNNs) and CNNs are two examples of deep learning approaches that have been used to enhance accuracy, resilience, and efficiency in a variety of applications. A richer comprehension of visual material has resulted from the integration of spatial and temporal data with semantic analysis. These developments have enormous potential for use in a variety of fields, influencing the direction of computer vision and its social effects.