Computer Vision Application

Computer vision applications leverage artificial intelligence to enable computers to "see" and interpret images and videos, aiming to automate tasks previously requiring human visual perception. Current research emphasizes improving model efficiency and accuracy through techniques like transfer learning, integrating diverse data sources (points and lines, multi-camera data), and employing advanced architectures such as Vision Transformers and refined convolutional neural networks. These advancements are driving progress in diverse fields, from autonomous driving and robotics to medical diagnosis and agricultural monitoring, by improving automation, accuracy, and efficiency in data analysis.