Real Time
Real-time processing focuses on developing systems capable of analyzing and responding to data instantaneously, crucial for applications demanding immediate feedback. Current research emphasizes efficient algorithms and model architectures, such as those based on deep learning, to reduce computational latency in diverse domains including robotics, healthcare, and AI-assisted tutoring. This field's advancements are driving progress in areas like autonomous navigation, personalized healthcare monitoring, and human-computer interaction, enabling more responsive and effective systems.
Papers
Real-time object detection and robotic manipulation for agriculture using a YOLO-based learning approach
Hongyu Zhao, Zezhi Tang, Zhenhong Li, Yi Dong, Yuancheng Si, Mingyang Lu, George Panoutsos
Real-time EEG-based Emotion Recognition Model using Principal Component Analysis and Tree-based Models for Neurohumanities
Miguel A. Blanco-Rios, Milton O. Candela-Leal, Cecilia Orozco-Romo, Paulina Remis-Serna, Carol S. Velez-Saboya, Jorge De-J. Lozoya-Santos, Manuel Cebral-Loureda, Mauricio A. Ramirez-Moreno