Facial Expression Recognition Based on Snaking Data Access and Pipeline Convolution Neural Network
- Resource Type
- Conference
- Authors
- Lin, Chi-Chang; Hsieh, Chia-Yu; Wu, Ping-Cheng; Chen, Ping-Chun; Xiao, You-Sheng; Fan, Yu-Cheng
- Source
- 2022 IET International Conference on Engineering Technologies and Applications (IET-ICETA) Engineering Technologies and Applications (IET-ICETA), 2022 IET International Conference on. :1-2 Oct, 2022
- Subject
- Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
General Topics for Engineers
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
Emotion recognition
Convolution
Face recognition
Pipelines
Neural networks
Character recognition
Integrated circuit modeling
facial expression recognition
fast convolution
neural networks
Winograd
- Language
In this paper, we proposed facial expression recognition based on snaking data access and pipeline convolution neural network. This paper performs an expression recognition system composed of fast convolution operations. We use Winograd algorithm to reduce the number of multipliers and design data reuse, pipeline and Snaking data access structures to increase the performance of the chip. Therefore, the chip can perform high-speed computing and achieve a well facial expression recognition rate.