Search Results - stacked denoising autoencoder network
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Deep learning for electrolysis process anode effect prediction based on long short-term memory network and stacked denoising autoencoder
ISSN: 1001-0521, 1867-7185Published: Beijing Nonferrous Metals Society of China 01.12.2024Published in Rare metals (01.12.2024)“… A stacked denoising autoencoder is utilized to denoise and extract features from a large number of long-period parameter data…”
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Wind turbine generator early fault diagnosis using LSTM-based stacked denoising autoencoder network and stacking algorithm
ISSN: 1543-5075, 1543-5083, 1543-5083Published: Taylor & Francis 01.09.2024Published in International journal of green energy (01.09.2024)“… Specifically, a multivariate spatiotemporal condition monitoring model (LSDAE) was established by combining the LSTM and SDAE networks, which can detect generator early anomalies through real-time monitoring the reconstruction residual…”
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Video surveillance image enhancement via a convolutional neural network and stacked denoising autoencoder
ISSN: 0941-0643, 1433-3058Published: London Springer London 01.02.2022Published in Neural computing & applications (01.02.2022)“…) and a denoising autoencoder, the image quality can be enhanced. The DLIE…”
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Automated atrial fibrillation classification based on denoising stacked autoencoder and optimized deep network
ISSN: 0957-4174, 1873-6793Published: Elsevier Ltd 15.12.2023Published in Expert systems with applications (15.12.2023)“… Denoising autoencoders (DAEs) utilising convolutional neural networks (CNNs) as backbones outperformed the other two DAE models…”
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Visual tracking based on stacked Denoising Autoencoder network with genetic algorithm optimization
ISSN: 1380-7501, 1573-7721Published: New York Springer US 01.02.2018Published in Multimedia tools and applications (01.02.2018)“… There are two training stages for the SDAE network: Layer-wise pre-training and fine-tuning. In the pre-training stage, a two-layer sparse-coded method is used to represent the input image, then a multi-level image feature descriptor is obtained…”
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Identification Method for Missing Cotter Pins in Catenary Systems Based on Stacked Denoising Autoencoder Network
ISSN: 1007-869XPublished: Urban Mass Transit Magazine Press 01.10.2024Published in Chengshi Guidao Jiaotong Yanjiu (01.10.2024)“… (stacked denoising autoencoder), thereby achieving efficient detection of missing cotter pins…”
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SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction
ISSN: 0893-6080, 1879-2782, 1879-2782Published: United States Elsevier Ltd 01.06.2020Published in Neural networks (01.06.2020)“…Complex network is a general model to represent the interactions within technological, social, information, and biological interaction…”
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Intelligent fault diagnosis method of rolling bearing based on stacked denoising autoencoder and convolutional neural network
ISSN: 0036-8792, 1758-5775Published: Bradford Emerald Publishing Limited 17.09.2020Published in Industrial lubrication and tribology (17.09.2020)“… To solve those problems, an intelligent fault diagnosis model based on stacked denoising autoencoder (SDAE…”
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Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering
ISSN: 1076-2787, 1099-0526Published: Cairo, Egypt Hindawi Publishing Corporation 26.07.2020Published in Complexity (New York, N.Y.) (26.07.2020)“…This paper presents a model based on stacked denoising autoencoders (SDAEs) in deep learning and adaptive affinity propagation (adAP…”
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Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network
ISSN: 2075-1702, 2075-1702Published: Basel MDPI AG 01.12.2021Published in Machines (Basel) (01.12.2021)“…This paper introduces a new intelligent fault diagnosis method based on stack pruning sparse denoising autoencoder and convolutional neural network (sPSDAE-CNN…”
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Demodulating Optical Wireless Communication of FBG Sensing with Turbulence-Caused Noise by Stacked Denoising Autoencoders and the Deep Belief Network
ISSN: 2079-9292, 2079-9292Published: Basel MDPI AG 01.10.2024Published in Electronics (Basel) (01.10.2024)“… 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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Traffic Image Analysis Based on Stacked Denoising Autoencoder Neural Network
ISSN: 2716-0858, 2715-9248Published: Pusat Penelitian dan Pengabdian Masyarakat (P3M), Politeknik Negeri Cilacap 29.12.2023Published in Journal of Innovation Information Technology and Application (29.12.2023)“…This study aims to explore major neural network models - Stacked Denoising Autoencoder (SDAE…”
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Network intrusion detection based on Contractive Sparse Stacked Denoising Autoencoder
ISSN: 2155-5052Published: IEEE 04.08.2021Published in IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (04.08.2021)“… identify and classify network intrusion data, this paper proposes a Contractive Sparse Stack Denoising Autoencoder(CSSDAE…”
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Conference Proceeding -
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Stepwise Inertial Intelligent Control of Wind Power for Frequency Regulation Based on Stacked Denoising Autoencoder and Deep Neural Network
ISSN: 1006-2467Published: Editorial Office of Journal of Shanghai Jiao Tong University 01.11.2023Published in Shànghăi jiāotōng dàxué xuébào (01.11.2023)“…Stepwise inertial control (SIC) provides a step-increase of power after load fluctuation, which can effectively prevent system frequency decline and ensure the…”
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Application of deep neural network with stacked denoising autoencoder for ECG signal classification
ISSN: 2721-5792, 2721-5792Published: 30.06.2024Published in Journal of Intelligent Decision Support System (IDSS) (30.06.2024)“…Applying deep neural networks with stacked denoising autoencoders (SDAEs) for ECG signal classification presents a promising approach for improving the accuracy of arrhythmia diagnosis…”
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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
ISSN: 1076-2787, 1099-0526Published: Cairo, Egypt Hindawi Publishing Corporation 02.11.2020Published in Complexity (New York, N.Y.) (02.11.2020)“… 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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Fully convolutional Deep Stacked Denoising Sparse Auto encoder network for partial face reconstruction
ISSN: 0031-3203, 1873-5142Published: Elsevier Ltd 01.10.2022Published in Pattern recognition (01.10.2022)“…•By using principle component analysis and linear regression method and re-identification to the DS-DSA network…”
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Stacked Denoising Autoencoder network for short-term prediction of electrical Algerian load
ISSN: 2576-3555Published: IEEE 29.06.2020Published in International Conference on Control, Decision and Information Technologies (Online) (29.06.2020)“… In this paper, time series models have been developed to provide an efficient forecast for electricity consumption in Algeria using Deep Neural Networks in the form of Stacked Denoising Autoencoder (SDAE…”
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Conference Proceeding -
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Partial Discharge Patterns Recognition of GIS with Denoising-stacked Autoencoder Networks
Published: IEEE 01.06.2020Published in 2020 5th Asia Conference on Power and Electrical Engineering (ACPEE) (01.06.2020)“… This paper proposes a pattern recognition classifier that directly and automatically selects and classifies fault features by denoising-stacked autoencoder…”
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Conference Proceeding -
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A Nonnegativity-Constraint Sparse Stacked Denoising Autoencoder for Anomaly Detection in Electric Power Communication Network
ISSN: 2155-5052Published: IEEE 27.10.2020Published in IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (27.10.2020)“… To deal with this problem, a nonnegativity-constraint sparse stacked denoising autoencoder…”
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Conference Proceeding