Computer Vision is one of the most important branches of artificial intelligence, aiming to enable computers to interpret and analyze images and videos in a way similar to human vision. Recent advances in artificial intelligence algorithms, particularly deep learning, have significantly improved the accuracy and performance of computer vision systems. Concept of Computer Vision Computer vision refers to a set of techniques and algorithms that allow computer systems to extract meaningful information from digital images. These processes include object recognition, pattern detection, scene analysis, and motion tracking. AI Algorithms in Computer Vision Modern computer vision heavily relies on artificial intelligence algorithms, especially artificial neural networks, and more specifically convolutional neural networks (CNNs). These networks have demonstrated high efficiency in image processing and feature extraction. CNNs process images through multiple layers, where each layer analyzes specific characteristics such as edges, shapes, and complex patterns. Role of Deep Learning Deep learning has significantly enhanced the performance of computer vision algorithms by training models on large datasets. This approach enables systems to learn automatically without explicit programming, improving their ability to generalize and adapt to new data.