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
VolTeMorph: Realtime, Controllable and Generalisable Animation of Volumetric Representations
Stephan J. Garbin, Marek Kowalski, Virginia Estellers, Stanislaw Szymanowicz, Shideh Rezaeifar, Jingjing Shen, Matthew Johnson, Julien Valentin
A Real-time Edge-AI System for Reef Surveys
Yang Li, Jiajun Liu, Brano Kusy, Ross Marchant, Brendan Do, Torsten Merz, Joey Crosswell, Andy Steven, Lachlan Tychsen-Smith, David Ahmedt-Aristizabal, Jeremy Oorloff, Peyman Moghadam, Russ Babcock, Megha Malpani, Ard Oerlemans
Voice Analysis for Stress Detection and Application in Virtual Reality to Improve Public Speaking in Real-time: A Review
Arushi, Roberto Dillon, Ai Ni Teoh, Denise Dillon