Search Results - "Deep-stacked denoising autoencoder"

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

“…SSDAE-NCL-based gearbox fault diagnosis. [Display omitted] •A novel selective DNN ensemble is proposed for gearbox fault diagnosis.•A selective SDAE with 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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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.•The performance of…”
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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

“…•The electroencephalogram (EEG) is used to evaluate human cognitive workload.•Inter-subject EEG modeling scheme is employed.•Approach of cascade ensemble of…”
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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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Optimal deep convolutional neural network based crop classification model on multispectral remote sensing images by Chamundeeswari, G., Srinivasan, S., Bharathi, S. Prasanna, Priya, P., Kannammal, G. Rajendra, Rajendran, Sasikumar

“…•Propose a new ODCNN-CCM model for crop classification on multispectral remote sensing images.•Employ WF based image preprocessing and RetinaNet model as a…”
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Biometric Finger Vein Recognition Using Evolutionary Algorithm with Deep Learning by Yamin, Mohammad, Gedeon, Tom, Bajaba, Saleh, M. Abusurrah, Mona

“…In recent years, the demand for biometric-based human recognition methods has drastically increased to meet the privacy and security requirements. Palm prints,…”
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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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A New Unsupervised Online Early Fault Detection Framework of Rolling Bearings Based on Granular Feature Forecasting by Liu, Keying, Mao, Wentao, Shi, Huadong, Liang, Xihui

“… If the offline monitoring data are available, a deep stacked denoising autoencoder (SDAE) network with domain adaptation is introduced to extract common feature…”
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Crop Classification on Hyperspectral Images Using Residual Network and Multi-Head Self-Attention Feature Extraction by Naga Saranya, N., Vivekanandhan, V., Al-Farouni, Mohammed, Shreyas, A V, Ranjith kumar, Gotte

“…Nowadays, hyperspectral imaging has empowered classification and prediction in many fields such as agriculture, land usage, tourism, etc. due to advancements…”
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Autoencoders as Weight Initialization of Deep Classification Networks Applied to Papillary Thyroid Carcinoma by Ferreira, Mafalda Falcao, Camacho, Rui, Teixeira, Luis Filipe

“… Previous work by Teixeira et al. compared different methods of Data Oversampling and Feature Reduction, as well as Deep (Stacked…”
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