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Found 7 papers, 1 papers with code
ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design
The ease of data collection and aggregation in ArchGym facilitates research in ML-aided architecture design space exploration.
Datasheets for Machine Learning Sensors: Towards Transparency, Auditability, and Responsibility for Intelligent Sensing
Machine learning (ML) sensors are enabling intelligence at the edge by empowering end-users with greater control over their data.
Is TinyML Sustainable? Assessing the Environmental Impacts of Machine Learning on Microcontrollers
This article discusses both the potential of these TinyML applications to address critical sustainability challenges, as well as the environmental footprint of this emerging technology.
FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning
Applications of machine learning (ML) are growing by the day for many unique and challenging scientific applications.
Machine Learning Sensors
Machine learning sensors represent a paradigm shift for the future of embedded machine learning applications.
Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots
Machine learning (ML) has become a pervasive tool across computing systems.
CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs
In this paper, we present CFU Playground: a full-stack open-source framework that enables rapid and iterative design and evaluation of machine learning (ML) accelerators for embedded ML systems.
