Behavior Detection

Behavior detection, using computer vision and machine learning, aims to automatically identify and classify actions or patterns in visual data, such as videos or images. Current research focuses on improving the accuracy and efficiency of detection across diverse applications, employing deep learning architectures like YOLO and its variants, along with other models such as Graph Convolutional Networks and self-contrastive learning approaches. This field is significant for its potential to enhance various sectors, including education (assessing student engagement), healthcare (early autism detection), and public safety (monitoring traffic and online behavior), by providing automated, objective assessments of behavior.