1D Convolutional Autoencoder-Based PPG and GSR Signals for Real-Time Emotion Classification-Reference-Cited by-同舟云学术

1D Convolutional Autoencoder-Based PPG and GSR Signals for Real-Time Emotion Classification

Published:2022 Issue: Volume:10 Page:91332-91345
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kang Dong-Hyun¹,Kim Deok-Hwan²^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Inha University, Incheon, South Korea

2. Department of Electronic Engineering, Inha University, Incheon, South Korea

Funder

Institute of Information and Communications Technology Planning and Evaluation (IITP) Grant through the Korean Government [Ministry of Science and ICT (MSIT)], XVoice: Multi-Modal Voice Meta Learning

Inha University Research Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09866042.pdf?arnumber=9866042

Reference53 articles.

1. A Multimodal Database for Affect Recognition and Implicit Tagging

2. DEAP: A Database for Emotion Analysis ;Using Physiological Signals

3. Utilizing Knowledge Distillation in Deep Learning for Classification of Chest X-Ray Abnormalities

4. Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding;han;arXiv 1510 00149 [cs],2015

5. Performance Analysis and CPU vs GPU Comparison for Deep Learning

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