Search Results - Deep-stacked denoising autoencoder~

A selective deep stacked denoising autoencoders ensemble with negative correlation learning for gearbox fault diagnosis by Yu, Jianbo

“… This paper proposes a selective stacked denoising autoencoders (SDAE) with negative correlation learning (NCL) (SSDAE-NCL…”
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Monitoring of complex profiles based on deep stacked denoising autoencoders by Chen, Shumei, Yu, Jianbo, Wang, Shijin

“…Fig. 4. Schematic diagram of the SDAE-based model for profile monitoring. [Display omitted] •DNN is developed for modelling complex profiles.•SDAE is effective…”
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Face recognition via Deep Stacked Denoising Sparse Autoencoders (DSDSA) by Görgel, Pelin, Simsek, Ahmet

“… In this paper, the proposed face recognition system namely Deep Stacked Denoising Sparse Autoencoders (DSDSA…”
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An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition by Wang, Zirui, Wang, Jun, Wang, Youren

“…•A new diagnostic model named SDAE-GAN is proposed.•The model combines Generative Adversarial Networks and Stacked Denoising Autoencoders…”
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Deep learning framework designed for high-performance lithium-ion batteries state monitoring by Takyi-Aninakwa, Paul, Wang, Shunli, Liu, Guangchen, Fernandez, Carlos, Kang, Wenbin, Song, Yingze

“… In this work, a deep-stacked denoising autoencoder is established for a long short-term memory model that incorporates a transfer learning mechanism to estimate and study the SOC from an electrochemical perspective…”
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Fully convolutional Deep Stacked Denoising Sparse Auto encoder network for partial face reconstruction by Dinesh, P.S., Manikandan, M.

“…•In this partial face detection (PFD) is used to overcome the challenges involved in face detection and reconstruction.•A novel PFD algorithm called Self-…”
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Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label by Xu, Fan, Tse, Wai tai Peter, Tse, Yiu Lun

“…Most deep learning models such as stacked autoencoder (SAE) and stacked denoising autoencoder (SDAE…”
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Stepwise Inertial Intelligent Control of Wind Power for Frequency Regulation Based on Stacked Denoising Autoencoder and Deep Neural Network by WANG Yalun, ZHOU Tao, CHEN Zhong, WANG Yi, QUAN Hao

“… In order to realize the optimal stepwise inertial fast control of wind power frequency regulation in load disturbance events, this paper introduces the deep learning algorithm and proposes a stepwise…”
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Inter-subject cognitive workload estimation based on a cascade ensemble of multilayer autoencoders by Zheng, Zhanpeng, Yin, Zhong, Wang, Yongxiong, Zhang, Jianhua

“…•Approach of cascade ensemble of multilayer autoencoders is proposed. Machine learning approaches can build a computational model to predict cognitive workload levels by using electroencephalogram (EEG…”
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Data augmentation versus noise compensation for x-vector speaker recognition systems in noisy environments by Mohammad Amini, Mohammad, Matrouf, Driss

“…The explosion of available speech data and new speaker modeling methods based on deep neural networks (DNN) have given the ability to develop more robust…”
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Deep feature fusion‐based stacked denoising autoencoder for tag recommendation systems by Fei, Zhengshun, Wang, Jinglong, Liu, Kangling, Attahi, Eric, Huang, Bingqiang

“…With the rapid development of artificial intelligence technology, commercial robots have gradually entered our daily lives. In order to promote product…”
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Automated atrial fibrillation classification based on denoising stacked autoencoder and optimized deep network by Singh, Prateek, Sharma, Ambalika, Maiya, Shreesha

“… With this in mind, the two-fold study is proposed, in which three denoising autoencoders for ECG signal pre-processing were evaluated and compared…”
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An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals by 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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The Performance of Deep Learning Algorithms on Automatic Pulmonary Nodule Detection and Classification Tested on Different Datasets That Are Not Derived from LIDC-IDRI: A Systematic Review by Li, Dana, Mikela Vilmun, Bolette, Frederik Carlsen, Jonathan, Albrecht-Beste, Elisabeth, Ammitzbøl Lauridsen, Carsten, Bachmann Nielsen, Michael, Lindskov Hansen, Kristoffer

“…The aim of this study was to systematically review the performance of deep learning technology in detecting and classifying pulmonary nodules on computed…”
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Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels by Zhang, Xiaodi, Li, Xin, Shu, Xin, Xu, Fan

“… In this paper, we use the stacked denoising autoencoder (SDAE) model in deep learning to construct HI directly from the microgrid power equipment of raw signals in bearings…”
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Deep Learning-Based Stacked Denoising and Autoencoder for ECG Heartbeat Classification by Nurmaini, Siti, Darmawahyuni, Annisa, Sakti Mukti, Akhmad Noviar, Rachmatullah, Muhammad Naufal, Firdaus, Firdaus, Tutuko, Bambang

“…The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia. However, the ECG signal is prone to contamination by different kinds…”
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Multi-source deep transfer learning with stacked denoising autoencoder and Wasserstein distance for wind power prediction in new wind farm by Xu, Haiyan, Hao, Wenguang, Zhao, Yong, Tian, Hongda

“…•Stacked denoising autoencoder is used to establish feature correlations between the source and target domain…”
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The pre-trained explainable deep learning model with stacked denoising autoencoders for slope stability analysis by Lin, Shan, Dong, Miao, Cao, Xitailang, Liang, Zenglong, Guo, Hongwei, Zheng, Hong

“… In this work, we proposed a deeply-integrated explainable pre-trained deep learning framework with stacked denoising autoencoders in the assessment of slope stability…”
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Demodulating Optical Wireless Communication of FBG Sensing with Turbulence-Caused Noise by Stacked Denoising Autoencoders and the Deep Belief Network by Bogale, Shegaw Demessie, Yao, Cheng-Kai, Manie, Yibeltal Chanie, Dehnaw, Amare Mulatie, Tefera, Minyechil Alehegn, Li, Wei-Long, Zhong, Zi-Gui, Peng, Peng-Chun

“… This work aims to deep denoise sensed signals from fiber Bragg grating (FBG) sensors based on FSO link transmission using advanced denoising deep learning techniques, such as stacked denoising autoencoders (SDAE…”
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A Wireless Positioning Method Based on Deep Neural Network by LIU Kan,ZHANG Wei,ZHANG Weidong,ZHANG Youmei,GU Jianjun

“…).It uses a four-layer Deep Neural Network(DNN) structure pre-trained by Stacked Denoising Autoencoder(SDA…”
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