Expression Recognition Method Using Improved VGG16 Network Model in Robot Interaction
Aiming at the problems of poor representation ability and less feature data when traditional expression recognition methods are applied to intelligent applications, an expression recognition method based on improved VGG16 network is proposed. Firstly, the VGG16 network is improved by using large con...
Saved in:
Main Author: | Shengbin Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Journal of Robotics |
Online Access: | http://dx.doi.org/10.1155/2021/9326695 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education
by: Phat Nguyen Huu, et al.
Published: (2021-01-01) -
Training VGG16, MobileNetV1 and Simple CNN Models from Scratch for Balinese Inscription Recognition
by: Ida Ayu Putu Febri Imawati, et al.
Published: (2025-01-01) -
VGG-16, VGG-16 With Random Forest, Resnet50 With SVM, and EfficientNetB0 With XGBoost-Enhancing Bone Fracture Classification in X-Ray Using Deep Learning Models
by: Spoorthy Torne, et al.
Published: (2025-01-01) -
Optimization of VGG-16 Accuracy for Fingerprint Pattern Imager Classification
by: Agus Andreansyah, et al.
Published: (2025-01-01) -
Attention-enhanced corn disease diagnosis using few-shot learning and VGG16
by: Ruchi Rani, et al.
Published: (2025-06-01)