06
Sep
Artificial intelligence (AI) has made incredible progress, from deciphering the nuances of written language to interpreting the rich complexity of images, videos, and even LiDAR data. This transition has advanced computer vision (CV), enabling machines to “see” and perceive the visual world. Extracting intelligence from visual data is often more intricate than processing text. This is due to factors like the high dimensionality of visual data, occlusion, perspective, and lighting conditions of images, as well as relative complexity in feature extraction. Machine learning (ML) in CV has additional challenges, such as the non-availability of enough relevant images for pre-training, the…