Výsledky vyhľadávania - Cascade stacked autoencoder neural network
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Cascade stacked autoencoder neural network for intrusion detection in CAN-FD vehicular network
ISSN: 0950-7051Vydavateľské údaje: Elsevier B.V 04.11.2025Vydané v Knowledge-based systems (04.11.2025)“…In this work, an Intrusion Detection System (IDS) for Controller Area Network with Flexible Data Rate (CAN-FD…”
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Multi-label classification using a cascade of stacked autoencoder and extreme learning machines
ISSN: 0925-2312, 1872-8286Vydavateľské údaje: Elsevier B.V 17.09.2019Vydané v Neurocomputing (Amsterdam) (17.09.2019)“…•Three phase cascade of neural networks for multi-label classification.•Network model includes stacked autoencoders and extreme learning machines…”
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CDAE: A Cascade of Denoising Autoencoders for Noise Reduction in the Clustering of Single-Particle Cryo-EM Images
ISSN: 1664-8021, 1664-8021Vydavateľské údaje: Switzerland Frontiers Media S.A 20.01.2021Vydané v Frontiers in genetics (20.01.2021)“… In this study, we design an effective cryo-EM image denoising model, CDAE, i.e., a cascade of denoising autoencoders…”
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Prediction of miRNA–Disease Associations by Cascade Forest Model Based on Stacked Autoencoder
ISSN: 1420-3049, 1420-3049Vydavateľské údaje: Switzerland MDPI AG 27.06.2023Vydané v Molecules (Basel, Switzerland) (27.06.2023)“… Then, the stacked autoencoder is applied for obtaining the underlying feature representation. Finally, the modified cascade forest model is employed to complete…”
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Stacked encoded cascade error feedback deep extreme learning machine network for manufacturing order completion time
ISSN: 0956-5515, 1572-8145Vydavateľské údaje: New York Springer US 01.02.2025Vydané v Journal of intelligent manufacturing (01.02.2025)“… To predict the OCT, firstly, the stacked autoencoder is used to generate input connection weights for the network by learning a deep representation of the real…”
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Sparse stacked autoencoder network for complex system monitoring with industrial applications
ISSN: 0960-0779, 1873-2887Vydavateľské údaje: Elsevier Ltd 01.08.2020Vydané v Chaos, solitons and fractals (01.08.2020)“…•A fault classification and isolation method based on SAE is proposed for complex system.•Deep learning model formed by AE with sparse and regular constraints…”
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Infomax-based deep autoencoder network for recognition of multi-element geochemical anomalies linked to mineralization
ISSN: 0098-3004, 1873-7803Vydavateľské údaje: Elsevier Ltd 01.06.2023Vydané v Computers & geosciences (01.06.2023)“…In recent years, deep autoencoder networks (DANs) have shown enormous potential to achieve state-of-the-art performance for recognizing multi-element geochemical anomalies related to mineralization…”
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Cascade neural network-based joint sampling and reconstruction for image compressed sensing
ISSN: 1863-1703, 1863-1711Vydavateľské údaje: London Springer London 01.02.2022Vydané v Signal, image and video processing (01.02.2022)“… In this paper, we propose a unified framework, which jointly considers the sampling and reconstruction process for image compressive sensing based on well-designed cascade neural networks…”
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CSO-CNN: circulatory system optimization-based cascade region CNN for fault estimation and driver behavior detection
ISSN: 1863-1703, 1863-1711Vydavateľské údaje: London Springer London 01.09.2023Vydané v Signal, image and video processing (01.09.2023)“… Taking these into consideration his paper proposes a novel cascade region convolutional neural network-based circulatory system optimization algorithm (CRCNN++ based CSO…”
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A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data
ISSN: 1471-2105, 1471-2105Vydavateľské údaje: London BioMed Central 28.10.2019Vydané v BMC bioinformatics (28.10.2019)“… Stacked autoencoder (SAE) is used to learn high-level representations in each omics data, then the complex representations are learned by integrating…”
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Target Detection in Clutter/Interference Regions Based on Deep Feature Fusion for HFSWR
ISSN: 1939-1404, 2151-1535“… The algorithm has two stages: preprocessing and target detection. In the preprocessing stage, faster region-based convolutional neural networks Faster R-CNN are designed…”Vydavateľské údaje: Piscataway IEEE 2021
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Breast cancer cell nuclei classification in histopathology images using deep neural networks
ISSN: 1861-6410, 1861-6429, 1861-6429Vydavateľské údaje: Cham Springer International Publishing 01.02.2018Vydané v International journal for computer assisted radiology and surgery (01.02.2018)“… To address this challenge, this paper aims to present a novel deep neural network which performs representation learning and cell nuclei recognition in an end-to-end manner…”
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An ELM-based Deep SDAE Ensemble for Inter-Subject Cognitive Workload Estimation with Physiological Signals
ISSN: 1934-1768Vydavateľské údaje: Technical Committee on Control Theory, Chinese Association of Automation 01.07.2020Vydané v Chinese Control Conference (01.07.2020)“… This study proposes an inter-subject CW classifier, extreme learning machine (ELM)-based deep stacked denoising autoencoder ensemble (ED-SDAE…”
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Konferenčný príspevok.. -
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JSRNN: Joint Sampling and Reconstruction Neural Networks for High Quality Image Compressed Sensing
ISSN: 2331-8422Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 11.11.2022Vydané v arXiv.org (11.11.2022)“… In the reconstruction sub-network, a cascade network combining stacked denoising autoencoder…”
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Parallel Multistage Wide Neural Network
ISSN: 2162-237X, 2162-2388, 2162-2388Vydavateľské údaje: United States IEEE 01.08.2023Vydané v IEEE transaction on neural networks and learning systems (01.08.2023)“… (RBF) networks, and knowledge transfer (FDRK). In this article, a parallel multistage wide neural network (PMWNN) is presented…”
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Australia's long-term electricity demand forecasting using deep neural networks
ISSN: 2331-8422Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 10.01.2018Vydané v arXiv.org (10.01.2018)“… A stacked autoencoder is used in combination with multilayer perceptrons or cascade-forward multilayer perceptrons to predict the nation-wide electricity consumption rates for 1-24 months ahead of time…”
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