: On-Device Real-Time Deep Reinforcement Learning for Autonomous Robotics
Autonomous robotic systems, like autonomous vehicles and robotic search and rescue,
require efficient on-device training for continuous adaptation of Deep Reinforcement …
require efficient on-device training for continuous adaptation of Deep Reinforcement …
Red: A systematic real-time scheduling approach for robotic environmental dynamics
Intelligent robots are designed to effectively navigate dynamic and unpredictable
environments laden with moving mechanical elements and objects. Such environment …
environments laden with moving mechanical elements and objects. Such environment …
IOTeeth: Intra-Oral Teeth Sensing System for Dental Occlusal Diseases Recognition
While occlusal diseases-the main cause of tooth loss--significantly impact patients' teeth and
well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing …
well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing …
Genie: Smart ROS-based Caching for Connected Autonomous Robots
Despite the promising future of autonomous robots, several key issues currently remain that
can lead to compromised performance and safety. One such issue is latency, where we find …
can lead to compromised performance and safety. One such issue is latency, where we find …
Distantly-Supervised Joint Entity and Relation Extraction with Noise-Robust Learning
Joint entity and relation extraction is a process that identifies entity pairs and their relations
using a single model. We focus on the problem of training these models on distantly-labeled …
using a single model. We focus on the problem of training these models on distantly-labeled …