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Development of a hand pose recognition system on an embedded computer using CNNs

Computer Vision and Pattern Recognition 2019-10-25 v1

Abstract

Demand of hand pose recognition systems are growing in the last years in technologies like human-machine interfaces. This work suggests an approach for hand pose recognition in embedded computers using hand tracking and CNNs. Results show a fast time response with an accuracy of 94.50% and low power consumption.

Keywords

Cite

@article{arxiv.1910.11100,
  title  = {Development of a hand pose recognition system on an embedded computer using CNNs},
  author = {Dennis Núñez Fernández},
  journal= {arXiv preprint arXiv:1910.11100},
  year   = {2019}
}

Comments

LatinX in AI Research at NeurIPS 2019

R2 v1 2026-06-23T11:53:41.319Z