Computer vision has not become a sub-field of deep learning, but deep learning has significantly influenced and advanced the field. Computer vision encompasses a broad range of techniques for interpreting images and videos, including traditional methods like edge detection and modern deep learning approaches like convolutional neural networks (CNNs).
Deep learning has revolutionized computer vision by enabling more accurate and automated feature extraction, leading to breakthroughs in tasks such as object detection, facial recognition, and semantic segmentation. However, traditional methods and hybrid approaches are still used in specific scenarios.
Thus, while deep learning dominates current research and applications, computer vision remains a broader discipline that includes both classical algorithms and cutting-edge neural networks.