Revolutionizing Technology: Advancements, Challenges, and Future of Computer Vision

Computer vision is an active subfield of AI that empowers machines to analyse graphic information from the physical environment. It starts from simple image processing up to modern-day AI enabled deep learning systems. This field is widely used in healthcare (tumor detection, medical imaging), automobile industry (object and lane detection), and retail industry (visual search, quality inspection). The paradigms of Vision Transformers (ViTs) and self-supervised learning are shifting, as new approaches to scalability and performance issues arise. There are still considerable challenges, such as, data collection, computational resources and issues related to bias and privacy. Techniques such as model pruning, federated learning, explainable artificial intelligence (XAI) are being worked out to improve Fairness. The emerging trends for further developments are MIMAC, Real time edge computing, and Ethical AI to promote the proper implementation of the system. With the integration of other fields in AI and by solving current issues, computer vision is ready to revolutionize industries and people’s lives.