Multiscale Feature Fusion Attention Lightweight Facial Expression Recognition
Facial expression recognition based on residual networks is important for technologies related to space human-robot interaction and collaboration but suffers from low accuracy and slow computation in complex network structures. To solve these problems, this paper proposes a multiscale feature fusion...
Saved in:
| Main Authors: | Jinyuan Ni, Xinyue Zhang, Jianxun Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/6523234 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
CAGNet: A Network Combining Multiscale Feature Aggregation and Attention Mechanisms for Intelligent Facial Expression Recognition in Human-Robot Interaction
by: Dengpan Zhang, et al.
Published: (2025-06-01) -
PAtt-Lite: Lightweight Patch and Attention MobileNet for Challenging Facial Expression Recognition
by: Jia Le Ngwe, et al.
Published: (2024-01-01) -
Facial expression recognition using visible and IR by early fusion of deep learning with attention mechanism
by: Muhammad Tahir Naseem, et al.
Published: (2025-03-01) -
AttentionEP: Predicting essential proteins via fusion of multiscale features by attention mechanisms
by: Chuanyan Wu, et al.
Published: (2024-12-01) -
Multiscale feature cross‐layer fusion remote sensing target detection method
by: Yuting Lin, et al.
Published: (2023-03-01)