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 BDI Agents: a model and its implementation
Andrea Traldi, Francesco Bruschetti, Marco Robol, Marco Roveri, Paolo Giorgini
Real Time On Sensor Gait Phase Detection with 0.5KB Deep Learning Model
Yi-An Chen, Jien-De Sui, Tian-Sheuan Chang
A Real Time 1280x720 Object Detection Chip With 585MB/s Memory Traffic
Kuo-Wei Chang, Hsu-Tung Shih, Tian-Sheuan Chang, Shang-Hong Tsai, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang
midiVERTO: A Web Application to Visualize Tonality in Real Time
Daniel Harasim, Giovanni Affatato, Fabian C. Moss
Brain inspired neuronal silencing mechanism to enable reliable sequence identification
Shiri Hodassman, Yuval Meir, Karin Kisos, Itamar Ben-Noam, Yael Tugendhaft, Amir Goldental, Roni Vardi, Ido Kanter