Computer Vision Approach

Computer vision employs image analysis and machine learning to enable computers to "see" and interpret visual information, addressing diverse objectives like object detection, classification, and motion analysis. Current research heavily utilizes deep learning architectures, such as convolutional neural networks (CNNs) including ResNet, MobileNet, and YOLO, along with recurrent neural networks (RNNs) like LSTMs, and transformers, to achieve high accuracy in various applications. This field significantly impacts numerous sectors, from autonomous driving and maritime safety to medical diagnostics, agricultural monitoring, and even the analysis of human behavior and disease progression, offering improved efficiency and accuracy in data analysis and decision-making.