Výsledky vyhledávání - "autoencoder networks"

Improving the repeatability of two-rate model parameter estimations by using autoencoder networks Autor Ozdemir, Murat C, Eggert, Thomas, Straube, Andreas

“… In this paper, we collected time-series data from an experimental paradigm involving repeated training and investigated the effect of various cleaning methods, including an autoencoder network (AE…”
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Enhancing the Myoelectric Pattern Recognition Robustness to Electrode Shift by an Autoencoder-Based Feature Calibrator Autor Gao, Ge, Li, Yao, Liu, Yunfei, Zhang, Xu, Ruan, Yuwen

“… Subsequently, the flattened shifted view features serve as input for the autoencoder network, facilitating the model to learn a more resilient feature representation based…”
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Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network Autor Gao, Ge, Zhang, Xu, Chen, Xiang, Chen, Zhang

“…The objective of this work is to develop a novel myoelectric pattern recognition (MPR) method to mitigate the concurrent interference of electrode shift and…”
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Self-supervised autoencoder network for robust heart rate extraction from noisy photoplethysmogram: Applying blind source separation to biosignal analysis Autor Webster, Matthew B., Lee, Dongheon, Lee, Joonnyong

“… The trained network is then applied to a noisy PPG dataset collected during the daily activities of nine subjects and a surgical dataset comprising 4,681 patients…”
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Spatiotemporal Graph Autoencoder Network for Skeleton-Based Human Action Recognition Autor Abduljalil, Hosam, Elhayek, Ahmed, Marish Ali, Abdullah, Alsolami, Fawaz

“… In this study, we propose a novel, highly accurate spatiotemporal graph autoencoder network for HAR, designated as GA-GCN…”
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Brain fingerprinting and cognitive behavior predicting using functional connectome of high inter-subject variability Autor Lu, Jiayu, Yan, Tianyi, Yang, Lan, Zhang, Xi, Li, Jiaxin, Li, Dandan, Xiang, Jie, Wang, Bin

“…•High inter-subject variability for brain fingerprinting and cognitive behavior predicting…”
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Rejecting Novel Motions in High-Density Myoelectric Pattern Recognition Using Hybrid Neural Networks Autor Wu, Le, Chen, Xun, Chen, Xiang, Zhang, Xu

“…, a convolutional neural network (CNN) and autoencoder networks. In the framework, the CNN was first used to extract spatio-temporal information conveyed in the sEMG data recorded via high-density (HD…”
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Functional connectome fingerprinting: Identifying individuals and predicting cognitive functions via autoencoder Autor Cai, Biao, Zhang, Gemeng, Zhang, Aiying, Xiao, Li, Hu, Wenxing, Stephen, Julia M., Wilson, Tony W., Calhoun, Vince D., Wang, Yu‐Ping

“… In this paper, we propose to enhance the uniqueness of individual connectome based on an autoencoder network…”
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Facial Image Denoising Using Convolutional Autoencoder Network Autor Tun, Naing Min, Gavrilov, Alexander I., Tun, Nyan Linn

“… In this paper, we show that the solution of denoising process using the autoencoder networks based on the ORL face database…”
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Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-Ground Biomass Autor Shao, Zhenfeng, Zhang, Linjing, Wang, Lei

“… However, field data are limited in remote and unmanaged areas. In addition, optical reflectance usually saturates at high-density biomass level and is subject to cloud contaminations…”
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Industrial Process Fault Detection with Multi-View Feature Fusion Attention Mechanism Assisted Autoencoder Network Autor Tong, Yifan, Wang, Zhaojing, Yan, Xiaoyun, Hu, Xinrong, Li, Lijun

“… To address this gap, a novel fault detection framework is introduced in this study, leveraging a Multi-View Feature Fusion At-tention Mechanism Assisted Autoencoder Network (MFA-AE…”
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Artificial Intelligence in Fluorescence Lifetime Imaging Ophthalmoscopy (FLIO) Data Analysis—Toward Retinal Metabolic Diagnostics Autor Thiemann, Natalie, Sonntag, Svenja Rebecca, Kreikenbohm, Marie, Böhmerle, Giulia, Stagge, Jessica, Grisanti, Salvatore, Martinetz, Thomas, Miura, Yoko

“…) and autoencoder networks. The SVM was the only tested AI method, which was able to distinguish τ…”
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Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders Autor Sood, Meemansa, Sahay, Akrishta, Karki, Reagon, Emon, Mohammad Asif, Vrooman, Henri, Hofmann-Apitius, Martin, Fröhlich, Holger

“…Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant…”
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Multimodal Representation Learning for Alzheimer's Disease Diagnosis Autor Fan, Lian-xi, Liu, Yan-bei, Wang, Wen, Geng, Lei, Wu, Jun, Zhang, Fang, Xiao, Zhi-tao

“… no cure.Its early diagnosis and treatment have always been the focus of attention.The neuroimaging data of subjects has an important auxiliary role in the diagnosis…”
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Dynamic historical information incorporated attention deep learning model for industrial soft sensor modeling Autor Wang, Yalin, Liu, Diju, Liu, Chenliang, Yuan, Xiaofeng, Wang, Kai, Yang, Chunhua

“… To combat this issue, a novel attention-based dynamic stacked autoencoder networks (AD-SAE) for soft sensor modeling is proposed in this paper…”
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Speech Enhancement for Hearing Impaired Based on Bandpass Filters and a Compound Deep Denoising Autoencoder Autor 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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Functional Connectivity Networks with Latent Distributions for Mild Cognitive Impairment Identification Autor Tang, Qiling, Lu, Yuhong, Cai, Bilian, Wang, Yan

“… Due to the complexity and variability of rs-fMRI signal, we consider it as a random variable, and utilize variational autoencoder networks to encode it as a confidence distribution in the latent…”
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Mechanisms of Categorization in Infancy Autor Mareschal, Denis, French, Robert

“…‐month‐old infants (Younger, 1985). Simple autoencoder networks were exposed to the same stimuli used to test 10‐month‐olds…”
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Surface-based Multi-Axis Longitudinal Disentanglement Using Contrastive Learning for Alzheimer's Disease Autor Zhang, Jianwei, Shi, Yonggang

“… Recent advancements in deep learning have catalyzed the development of disentanglement techniques in Autoencoder networks, aiming to segregate longitudinal changes attributable to aging…”
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BrainSTEAM: A Practical Pipeline for Connectome-based fMRI Analysis towards Subject Classification Autor Li, Alexis, Yang, Yi, Cui, Hejie, Yang, Carl

“… To address such challenge, this study proposes BrainSTEAM, an integrated framework featuring a spatio-temporal module that consists of an EdgeConv GNN model, an autoencoder network, and a Mixup strategy…”
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