From the organization making the announcement. Primary source, but consider their incentives.
EMBridge: Enhancing Gesture Generalization from EMG Signals through Cross-Modal Representation Learning
Hand gesture classification using high-quality structured data such as videos, im- ages, and hand skeletons is a well-explored problem in computer vision. Alterna- tively, leveraging low-power,...
Apple Machine Learning··~4 min read
2-Minute Brief
According to Apple Machine Learning: Hand gesture classification using high-quality structured data such as videos, im- ages, and hand skeletons is a well-explored problem in computer vision. Alterna- tively, leveraging low-power, cost-effective bio-signals, e.g., surface electromyo- graphy (sEMG), allows for continuous gesture prediction on wearable devices. In this work, we aim to enhance EMG representation quality by aligning it with embeddings obtained from structured, high-quality modalities that provide richer semantic guidan
EMBridge: Enhancing Gesture Generalization from EMG Signals through Cross-Modal Representation Learning
TLDR
Hand gesture classification using high-quality structured data such as videos, im- ages, and hand skeletons is a well-explored problem in computer vision. Alterna- tively, leveraging low-power,...
2-Minute Brief
According to Apple Machine Learning: Hand gesture classification using high-quality structured data such as videos, im- ages, and hand skeletons is a well-explored problem in computer vision. Alterna- tively, leveraging low-power, cost-effective bio-signals, e.g., surface electromyo- graphy (sEMG), allows for continuous gesture prediction on wearable devices. In this work, we aim to enhance EMG representation quality by aligning it with embeddings obtained from structured, high-quality modalities that provide richer semantic guidan