A Resource Efficient Integer-Arithmetic-Only FPGA-Based CNN Accelerator for Real-Time Facial Emotion Recognition

A Resource Efficient Integer-Arithmetic-Only FPGA-Based CNN Accelerator for Real-Time Facial Emotion Recognition

Recently, many researches have been conducted on recognition of facial emotion using convolutional neural networks (CNNs), which show excellent performance in computer vision. To obtain a high classification accuracy, a CNN architecture with many parameters and high computational complexity is requi...

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Bibliographic Details
Main Authors: Jaemyung Kim, Jin-Ku Kang, Yongwoo Kim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Emotion recognition
convolutional neural network
quantization
accelerator
FPGA
Online Access:https://ieeexplore.ieee.org/document/9493194/

Internet

https://ieeexplore.ieee.org/document/9493194/

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