Výsledky vyhledávání - "Stacked Denoising Autoencoder"

Semi-Supervised Cross-Subject Emotion Recognition Based on Stacked Denoising Autoencoder Architecture Using a Fusion of Multi-Modal Physiological Signals Autor Luo, Junhai, Tian, Yuxin, Yu, Hang, Chen, Yu, Wu, Man

“… To circumvent the labor of artificially designing features, we propose to acquire affective and robust representations automatically through the Stacked Denoising Autoencoder (SDA…”
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Continuous Estimation of Upper Limb Joint Angle Based on Stacked Denoising Autoencoder Autor Wen, Liqun, Li, Donglin, Pei, Xinglong, Zhang, Yan, Wang, Jianhui

“…; then, a stacked denoising autoencoder (SDAE) network is constructed to encode the initial set of sEMG features in low dimensions…”
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Recognition of Cognitive Task Load levels using single channel EEG and Stacked Denoising Autoencoder Autor Yin, Zhong, Zhang, Jianhua

“… is particularly challenging as EEG is characterized by individual dependency and nonstationarity. In this paper, a deep learning model designed by Stacked Denoising AutoEncoder…”
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AIMAFE: Autism spectrum disorder identification with multi-atlas deep feature representation and ensemble learning Autor Wang, Yufei, Wang, Jianxin, Wu, Fang-Xiang, Hayrat, Rahmatjan, Liu, Jin

“…•Multi-atlas functional connectivity is calculated as the original feature representation.•Multi-atlas deep feature representation is extracted by a deep…”
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Inter-subject cognitive workload estimation based on a cascade ensemble of multilayer autoencoders Autor Zheng, Zhanpeng, Yin, Zhong, Wang, Yongxiong, Zhang, Jianhua

“…•The electroencephalogram (EEG) is used to evaluate human cognitive workload.•Inter-subject EEG modeling scheme is employed…”
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Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders Autor Yang, Shuo, Yin, Zhong, Wang, Yagang, Zhang, Wei, Wang, Yongxiong, Zhang, Jianhua

“…). To determine personalized properties in high dimensional EEG indicators, we introduce a feature mapping layer in stacked denoising autoencoder (SDAE…”
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An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals Autor Zheng, Zhanpeng, Yin, Zhong, Zhang, Jianhua

“… This study proposes an inter-subject CW classifier, extreme learning machine (ELM)-based deep stacked denoising autoencoder ensemble (ED-SDAE…”
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Deep feature learning for pulmonary nodule classification in a lung CT Autor Bum-Chae Kim, Yu Sub Sung, Heung-Il Suk

“… To validate the effectiveness of the proposed method, we performed experiments on our in-house dataset of 20 subjects…”
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Breast cancer cell nuclei classification in histopathology images using deep neural networks Autor Feng, Yangqin, Zhang, Lei, Yi, Zhang

“… Methods The proposed model hierarchically maps raw medical images into a latent space in which robustness is achieved by employing a stacked denoising autoencoder…”
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Deep similarity learning for multimodal medical images Autor Cheng, Xi, Zhang, Li, Zheng, Yefeng

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Machine Learning for Diabetes and Mortality Risk Prediction from Electronic Health Records Autor Alhassan, Zakhriya Nasser H

“…Data science can provide invaluable tools to better exploit healthcare data to improve patient outcomes and increase cost-effectiveness. Today, electronic…”
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Hybrid Neural Network mixed with Random Forests and Perlin noise Autor Mengfei Wang, Fengqin Zhang, Hua Guan, Xiaoqing Li, Guirong Chen, Tengyao Li, Xi Xi

“… In this paper, a deep neural network mixed with random forests, Stacked Denoising Autoencoder and Multilayer Perception is proposed to improve the classification effect of mixed features input…”
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Affective states classification using EEG and semi-supervised deep learning approaches Autor Haiyan Xu, Plataniotis, Konstantinos N.

“… and the affective states expression. To investigate on such correlation, two types of semi-supervised deep learning approaches, stacked denoising autoencoder…”
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Indiv-Brain: Individualized Brain Network Partition Learned from Individual fMRI Data using Deep Clustering with Vertex-level Attention Autor Guo, Zhitao, Duan, Yongjie, Xing, Le, Zhao, Xiaojie, Yao, Li, Long, Zhiying

“… Moreover, some studies trained models on a group of subjects to guide individual network partitioning…”
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