Suchergebnisse - compressed autoencoder

High-precision detection of dibutyl hydroxytoluene in edible oil via convolutional autoencoder compressed Fourier-transform near-infrared spectroscopy von Deng, Jihong, Chen, Zhenyu, Jiang, Hui, Chen, Quansheng

“… In this study, a pioneering detection approach involving the use of a one-dimensional convolutional autoencoder (1D-CAE …”
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Orthogonal features-based EEG signal denoising using fractionally compressed autoencoder von Nagar, Subham, Kumar, Ahlad, Swamy, M.N.S.

“… •We introduce a fractionally based compressed auto-encoder to address the problem of EEG Signal denoising …”
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CAFNet: Compressed Autoencoder-based Federated Network for Anomaly Detection von Md Tayeen, Abu Saleh, Misra, Satyajayant, Cao, Huiping, Harikumar, Jayashree

“… In this work, we propose a Compressed Autoencoder-based Federated Network (CAFNet) framework for network anomaly detection to deal with the labeled data scarcity …”
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Cross-Modal Contrastive Masked AutoEncoder for Compressed Video Pre-Training von Li, Bing, Chen, Jiaxin, Li, Guohao, Zhang, Dongming, Bao, Xiuguo, Huang, Di

“… In this paper, we propose a novel Transformer based approach, namely Cross-modal Contrastive Masked AutoEncoder (C2MAE …”
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A sparse autoencoder compressed sensing method for acquiring the pressure array information of clothing von Han, Tao, Hao, Kuangrong, Ding, Yongsheng, Tang, Xuesong

“… In this paper, we integrate some ideas of sparse autoencoder of deep learning into compressed sensing (CS …”
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A Light-Weight and Robust Tensor Convolutional Autoencoder for Anomaly Detection von Li, Xiaocan, Xie, Kun, Wang, Xin, Xie, Gaogang, Li, Kenli, Cao, Jiannong, Zhang, Dafang, Wen, Jigang

“… -linear feature in the data. To address the issues, we propose a Robust Tensor Convolutional Autoencoder (RTCAE …”
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Masked autoencoder for highly compressed single-pixel imaging von Liu, Haiyan, Chang, Xuyang, Yan, Jun, Guo, Pengyu, Xu, Dong, Bian, Liheng

“… , we report a highly compressed single-pixel imaging technique with a decreased sampling ratio. This technique superimposes an occluded mask onto modulation patterns, realizing that only the unmasked region of the scene is modulated and acquired …”
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Intelligent bearing fault diagnosis based on Teager energy operator demodulation and multiscale compressed sensing deep autoencoder von Pei, Xinglong, Zheng, Xiaoyang, Wu, Jinliang

“… Accurate fault diagnosis is essential to ensure the stability and reliability of machine systems. Deep learning (DL) techniques have demonstrated potential in …”
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Constrained Autoencoder-Based Pulse Compressed Thermal Wave Imaging for Sub-Surface Defect Detection von Kaur, Kirandeep, Mulaveesala, Ravibabu, Mishra, Priyanka

“… Pulse compressed favourable thermal wave imaging is one of the widely used non-destructive testing techniques due to its excellent noise rejection capabilities …”
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A radar emitter structural identification method for complex conditions based on compressed sensing and an autoencoder: A radar emitter structural identification method for complex conditions based von Song, Yu, Zhang, Wei, Yang, Yaozu, Zhang, Xin, Jiang, Yilin

“… combining compressed sensing (CS) and a neural network is proposed. CS enables sparse signal compression by projecting high-dimensional signals into a lower-dimensional space …”
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Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN Autoencoder von Nagar, Subham, Kumar, Ahlad

“… This paper presents a fractional one-dimensional convolutional neural network (CNN) autoencoder for denoising the Electroencephalogram …”
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A radar emitter structural identification method for complex conditions based on compressed sensing and an autoencoder von Song, Yu, Zhang, Wei, Yang, Yaozu, Zhang, Xin, Jiang, Yilin

“… combining compressed sensing (CS) and a neural network is proposed. CS enables sparse signal compression by projecting high-dimensional signals into a lower-dimensional space …”
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Compressed Feedback Using AutoEncoder Based on Deep Learning for D2D Communication Networks von Ban, Tae-Won

“… In this paper, we propose a feedback reduction scheme based on AutoEncoder and deep reinforcement learning for frequency division duplex (FDD …”
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An autoencoder based formulation for compressed sensing reconstruction von Majumdar, Angshul

“… This work proposes a new formulation for image reconstruction based on the autoencoder framework …”
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The optimally designed autoencoder network for compressed sensing von Zhang, Zufan, Wu, Yunfeng, Gan, Chenquan, Zhu, Qingyi

“… To this end, a deep learning based stacked sparse denoising autoencoder compressed sensing (SSDAE_CS) model, which mainly consists of an encoder sub-network and a decoder sub-network, is proposed and analyzed in this paper …”
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Detection of Double Compressed AMR Audio Using Stacked Autoencoder von Luo, Da, Yang, Rui, Li, Bin, Huang, Jiwu

“… The detection of double compressed audio is one of the key issues in audio forensics. In this paper, we propose a framework for detecting double compressed AMR audio based on the stacked autoencoder (SAE …”
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Orthogonal Features-based EEG Signal Denoising using Fractionally Compressed AutoEncoder von Nagar, Subham, Kumar, Ahlad, Swamy, M N S

“… A fractional-based compressed auto-encoder architecture has been introduced to solve the problem of denoising electroencephalogram (EEG) signals …”
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Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder von Dwivedi, Sanjiv K., Tjärnberg, Andreas, Tegnér, Jesper, Gustafsson, Mika

“… Here we ask whether disease-relevant modules of genes can be discovered without prior knowledge of a biological network, instead training a deep autoencoder from large transcriptional data …”
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Motor PHM on Edge Computing with Anomaly Detection and Fault Severity Estimation through Compressed Data Using PCA and Autoencoder von Choi, Jong Hyun, Jang, Sung Kyu, Cho, Woon Hyung, Moon, Seokbae, Kim, Hyeongkeun

“… ) and an autoencoder (AE) encoder achieving effective data compression while preserving fault detection and severity estimation integrity …”
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Autoencoders for Compressed Transmission of Vehicular Data von John, George Eldho, G, Rajesh

“… In this paper, a data compression framework using the transmission of autoencoder(AE) models in vehicular sensor networks is proposed, where the comparable AE variants are analyzed …”
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