Authors: Ms. Dipti Rathod
Abstract: Artificial Intelligence (AI) has significantly transformed the field of computer vision by enabling machines to interpret and analyze visual data with high accuracy and efficiency. Computer vision, a major branch of AI, focuses on developing systems that can acquire, process, and understand images and videos in a manner similar to human vision. With the advancement of machine learning and deep learning techniques—particularly Convolutional Neural Networks (CNNs)—computer vision systems have achieved remarkable improvements in tasks such as image classification, object detection, facial recognition, and image segmentation. The integration of AI into computer vision has led to widespread applications across various industries, including healthcare, autonomous transportation, security and surveillance, retail, agriculture, and manufacturing. In healthcare, AI assists in medical image analysis and disease detection; in transportation, it powers self-driving vehicles; and in industrial sectors, it enhances quality inspection and automation. Despite these advancements, challenges such as the need for large labeled datasets, high computational costs, security risks, bias in algorithms, and ethical concerns remain significant issues in the computer industry. This research examines the role of artificial intelligence in the development of computer vision technology, explores its major applications, and highlights the key problems that need to be addressed. The study concludes that while AI-driven computer vision has revolutionized modern computing, continued research, ethical governance, and technological innovation are essential to fully realize its potential and ensure responsible implementation.
