Name
Title | ||
|---|---|---|
A Convolutional Neural Network With Multi-scale Kernel and Feature Fusion for sEMG-based Gesture Recognition |
Abstract | ||
|---|---|---|
The sEMG-based gesture recognition has great potential in human-computer interaction. However, the current approaches are far from optimal. In this paper, a novel convolutional neural network which combines the multi-scale kernal and feature fusion (MKFF-CNN) is proposed. This model could extract multi-scale features and make full use of these feature maps. One dataset called “gForce dataset” is r... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ROBIO54168.2021.9739426 | 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO) |
Keywords | DocType | ISBN |
Human computer interaction,Convolution,Conferences,Biomimetics,Biological system modeling,Gesture recognition,Feature extraction | Conference | 978-1-6654-0535-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lijun Han | 1 | 0 | 0.34 |
| Yongxiang Zou | 2 | 0 | 0.68 |
| Long Cheng | 3 | 1492 | 73.97 |