5 citations · 7 across the 3 of their papers we have counts for
5 papers
RobotPerf: An Open-Source, Vendor-Agnostic, Benchmarking Suite for Evaluating Robotics Computing System Performance
Víctor Mayoral-Vilches, Jason Jabbour, Yu-Shun Hsiao +16
We introduce RobotPerf, a vendor-agnostic benchmarking suite designed to evaluate robotics computing performance across a diverse range of hardware platforms using ROS 2 as its com…
Datasheets for Machine Learning Sensors
Matthew Stewart, Yuke Zhang, Pete Warden +12
Machine learning (ML) is becoming prevalent in embedded AI sensing systems. These "ML sensors" enable context-sensitive, real-time data collection and decision-making across divers…
Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers
Shvetank Prakash, Matthew Stewart, Colby Banbury +4
The sustained growth of carbon emissions and global waste elicits significant sustainability concerns for our environment's future. The growing Internet of Things (IoT) has the pot…
Widening Access to Applied Machine Learning with TinyML
Vijay Janapa Reddi, Brian Plancher, Susan Kennedy +21
Broadening access to both computational and educational resources is critical to diffusing machine-learning (ML) innovation. However, today, most ML resources and experts are siloe…
The evolving ecosystem of COVID-19 contact tracing applications
Benjamin Levy, Matthew Stewart
Since the outbreak of the novel coronavirus, COVID-19, there has been increased interest in the use of digital contact tracing as a means of stopping chains of viral transmission,…