Automatic Detection

Automatic detection encompasses a broad range of techniques using machine learning and computer vision to identify patterns and objects within various data types, aiming to automate tasks previously requiring manual effort. Current research focuses heavily on deep learning models, including convolutional neural networks (CNNs), vision transformers (ViTs), and large language models (LLMs), applied to diverse domains such as medical image analysis, text processing, and satellite imagery. These advancements offer significant potential for improving efficiency and accuracy in fields ranging from healthcare diagnostics and environmental monitoring to content moderation and cybersecurity, ultimately impacting various scientific disciplines and practical applications.