Suchergebnisse - "Denoising-Autoencoder"

Adaptive denoising autoencoder for robust fault detection von Li, Zixuan, Zhao, Haitao

“… Although denoising autoencoder can realize robust fault detection to a certain extent, its performance is limited by the addition of artificial noise, which refers to Gaussian noise or the dropout noise …”
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Atrial fibrillation detection on reconstructed photoplethysmography signals collected from a smartwatch using a denoising autoencoder von Mohagheghian, Fahimeh, Han, Dong, Ghetia, Om, Chen, Darren, Peitzsch, Andrew, Nishita, Nishat, Ding, Eric Y., Mensah Otabil, Edith, Noorishirazi, Kamran, Hamel, Alexander, Dickson, Emily L., DiMezza, Danielle, Tran, Khanh-Van, McManus, David D., Chon, Ki H.

“… ; however, the subjects were mostly in clinics or controlled settings with data collection lasting several minutes to at most several hours with minimal MNA …”
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Denoising Autoencoder-Based Feature Extraction to Robust SSVEP-Based BCIs von Chen, Yeou-Jiunn, Chen, Pei-Chung, Chen, Shih-Chung, Wu, Chung-Min

“… To suppress the effects of noises, a denoising autoencoder is proposed to extract the denoising features …”
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Noise Reduction in Photoplethysmography Signals using a Convolutional Denoising Autoencoder with Unconventional Training Scheme von Mohagheghian, Fahimeh, Han, Dong, Ghetia, Om, Peitzsch, Andrew, Nishita, Nishat, Nejad, Mahdi Pirayesh Shirazi, Ding, Eric Y., Noorishirazi, Kamran, Hamel, Alexander, Otabil, Edith Mensah, DiMezza, Danielle, Dickson, Emily L., Tran, Khanh-Van, McManus, David D., Chon, Ki H.

“… Objective : We propose an efficient approach based on a convolutional denoising autoencoder (CDA …”
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Semi-Supervised Cross-Subject Emotion Recognition Based on Stacked Denoising Autoencoder Architecture Using a Fusion of Multi-Modal Physiological Signals von 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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Lateral walking gait phase recognition for hip exoskeleton by denoising autoencoder-LSTM von Luo, Mingxiang, Dong, Xiaoli, Yu, Hongliu, Zhang, Mingming, Wu, Xinyu, Kobsiriphat, Worawarit, Wang, Jing-Xin, Cao, Wujing

“… This paper proposes a denoising autoencoder-LSTM (DAE-LSTM) algorithm for lateral walking gait recognition …”
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Continuous Estimation of Upper Limb Joint Angle Based on Stacked Denoising Autoencoder von 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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Speech Enhancement for Hearing Impaired Based on Bandpass Filters and a Compound Deep Denoising Autoencoder von AL-Taai, Raghad Yaseen Lazim, Wu, Xiaojun

“… ) multiple deep denoising autoencoder networks, with each working for a small specific enhancement task and learning to handle a subset of the whole …”
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Recognition of Cognitive Task Load levels using single channel EEG and Stacked Denoising Autoencoder von 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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Mood detection from daily conversational speech using denoising autoencoder and LSTM von Kun-Yi Huang, Chung-Hsien Wu, Ming-Hsiang Su, Hsiang-Chi Fu

“… Then, a denoising autoencoder (DAE) is used to construct an emotion conversion model to characterize the relationship between the perceived …”
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AIMAFE: Autism spectrum disorder identification with multi-atlas deep feature representation and ensemble learning von 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 von 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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Deep similarity learning for multimodal medical images von Cheng, Xi, Zhang, Li, Zheng, Yefeng

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Deep Learning Approaches for Detecting Freezing of Gait in Parkinson’s Disease Patients through On-Body Acceleration Sensors von Sigcha, Luis, Costa, Nélson, Pavón, Ignacio, Costa, Susana, Arezes, Pedro, López, Juan Manuel, De Arcas, Guillermo

“… Freezing of gait (FOG) is one of the most incapacitating motor symptoms in Parkinson’s disease (PD). The occurrence of FOG reduces the patients’ quality of …”
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Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders von 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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Automatic Eyeblink Artifact Removal from Single Channel EEG Signals Using One-Dimensional Convolutional Denoising Autoencoder von Acharjee, Raktim, Ahamed, Shaik Rafi

“… In this work, we proposed a one-dimensional Convolutional Denoising Autoencoder (CDAE) architecture to efficiently remove the eyeblink artifacts from the single channel EEG signals …”
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Deep learning-based motion artifact removal in functional near-infrared spectroscopy von Gao, Yuanyuan, Chao, Hanqing, Cavuoto, Lora, Yan, Pingkun, Kruger, Uwe, Norfleet, Jack E., Makled, Basiel A., Schwaitzberg, Steven, De, Suvranu, Intes, Xavier

“… To the best of our knowledge, this is the first investigation to report on the use of a denoising autoencoder (DAE …”
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On-Device Reliability Assessment and Prediction of Missing Photoplethysmographic Data Using Deep Neural Networks von Singha Roy, Monalisa, Roy, Biplab, Gupta, Rajarshi, Das Sharma, Kaushik

“… This paper describes an on-device reliability assessment from PPG measurements using a stack denoising autoencoder (SDAE …”
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Breast cancer cell nuclei classification in histopathology images using deep neural networks von 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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An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals von 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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