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Found 8 papers, 4 papers with code
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.
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse
We hope that our work will stimulate research and lead to the development of a new generation of ML systems for XR use cases.
DataPerf: Benchmarks for Data-Centric AI Development
Machine learning research has long focused on models rather than datasets, and prominent datasets are used for common ML tasks without regard to the breadth, difficulty, and faithfulness of the underlying problems.
Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots
Machine learning (ML) has become a pervasive tool across computing systems.
The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage
The People's Speech is a free-to-download 30, 000-hour and growing supervised conversational English speech recognition dataset licensed for academic and commercial usage under CC-BY-SA (with a CC-BY subset).
Widening Access to Applied Machine Learning with TinyML
Broadening access to both computational and educational resources is critical to diffusing machine-learning (ML) innovation.
Few-Shot Keyword Spotting in Any Language
With just five training examples, we fine-tune the embedding model for keyword spotting and achieve an average F1 score of 0. 75 on keyword classification for 180 new keywords unseen by the embedding model in these nine languages.
MLPerf Mobile Inference Benchmark
This paper presents the first industry-standard open-source machine learning (ML) benchmark to allow perfor mance and accuracy evaluation of mobile devices with different AI chips and software stacks.
