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Garbage In, Garbage Out - High-Quality Datasets for Edge ML Research

The EDGE AI FOUNDATION's Datasets & Benchmarks Working Group highlights the rapid progress in neural networks, particularly in cloud-based applications like image recognition and NLP, which benefited greatly from large, high-quality datasets. However, the constrained nature of edge AI devices necessitates smaller, more efficient models, yet a lack of suitable datasets hinders progress and realistic evaluation in this area. To address this, the Foundation aims to create and maintain a repository of production-grade, diverse, and well-annotated datasets for tiny and edge ML use cases, enabling…

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