Thermal Infrared

Thermal infrared (TIR) imaging leverages the heat signatures of objects to create images, offering advantages in various applications like wildlife monitoring and security. Current research focuses on improving object detection and tracking within TIR imagery, employing advanced deep learning architectures such as YOLO and transformer-based models, often incorporating techniques like domain adaptation to bridge the gap between limited TIR datasets and readily available RGB data. These advancements are crucial for enhancing the reliability and robustness of TIR-based systems across diverse applications, from autonomous vehicles to surveillance and rescue operations.