The Algorithm Based on Supervised Time Series Segmentation of Researching Dynamic Gesture Recognition
Author:
Affiliation:
1. Lanzhou Institute of Technology,College of Computer and Artificial Intelligence,Lanzhou,China,730050
Funder
Innovation Fund
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10140173/10140194/10140794.pdf?arnumber=10140794
Reference16 articles.
1. Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition With Multimodal Training
2. Real-time hand gesture detection and classification using convolutional neural networks;köpüklü;2019 14th IEEE International Conference on Automatic Face and Gesture Recognition,2019
3. Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-Based Optimization to Spiking Neural Networks
4. Research and implementation of gesture and motion understanding algorithm based on deep fusion network;wang;Beijing University of Posts and Telecommunications,2021
5. EgoGesture: A New Dataset and Benchmark for Egocentric Hand Gesture Recognition
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