Výsledky vyhledávání - sparse deep convolutional autoencoder

Self‐Attention‐Based Deep Convolutional Sparse Dense Autoencoder Model With Chebyshev‐Based Osprey Algorithm for Cardiovascular Disease Detection Autor Divya, N. J., Kumar, N. Suresh, Devi, R. Kanniga

“… This paper presents a deep convolutional neural network (CNN) for categorizing five CVDs using conventional 12‐lead ECG data…”
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SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography Autor Yousefi, Bardia, Akbari, Hamed, Hershman, Michelle, Kawakita, Satoru, Fernandes, Henrique C., Ibarra-Castanedo, Clemente, Ahadian, Samad, Maldague, Xavier P. V.

“…) prior to mammography. In this study, we propose a sparse deep convolutional autoencoder model named SPAER to extract low-dimensional deep thermomics to aid breast cancer diagnosis…”
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DOA estimation method for sparse arrays based on deep convolutional autoencoder and deep convolutional neural network Autor Guo, Shuhan, Zhang, Qin, Fu, Xiaolong, Zheng, Guimei, Zhou, Hao

“…This paper proposes a Direction-of-Arrival (DOA) estimation method based on Deep Convolutional Autoencoder (DCAE…”
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XAI-DSCSA: explainable-AI-based deep semi-supervised convolutional sparse autoencoder for facial expression recognition Autor Mohana, M., Subashini, P., Ghinea, George

“… as the Deep Semi-supervised Convolutional Sparse Autoencoder to address the aforementioned issues and enhance FER performance and prediction…”
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Online Public Opinion Situation Assessment by Deep Sparse Autoencoder and Time-Series Modeling Convolutional Neural Network Autor Sun, Wei, Xiao, Ran, Li, Xuanmo

“… This model employs Deep Sparse Autoencoder (DSAE) and Time-Series Modeling Convolutional Neural Networks (TBSMA-CNN…”
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TumorAwareNet: Deep representation learning with attention based sparse convolutional denoising autoencoder for brain tumor recognition Autor Bodapati, Jyostna Devi, Balaji, Bharadwaj Bagepalli

“…) images suitable for effective tumor recognition. The proposed model employs a Sparse Convolutional Denoising Autoencoder (SCDA…”
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Sparse Convolutional Denoising Autoencoders for Genotype Imputation Autor Chen, Junjie, Shi, Xinghua

“… To explore the performance of deep learning for genotype imputation, in this study, we propose a deep model called a sparse convolutional denoising autoencoder (SCDA…”
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EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder Autor Liu, Junxiu, Wu, Guopei, Luo, Yuling, Qiu, Senhui, Yang, Su, Li, Wei, Bi, Yifei

“…), Sparse Autoencoder (SAE), and Deep Neural Network (DNN) together. In the proposed network, the features extracted by the CNN are first sent to SAE for encoding and decoding…”
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Fully convolutional Deep Stacked Denoising Sparse Auto encoder network for partial face reconstruction Autor Dinesh, P.S., Manikandan, M.

“…•In this partial face detection (PFD) is used to overcome the challenges involved in face detection and reconstruction.•A novel PFD algorithm called Self-…”
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Predicting potential microbe-disease associations based on heterogeneous graph attention network and deep sparse autoencoder Autor Wang, Bo, Zhao, Wenlong, Du, Xiaoxin, Zhang, Jianfei, Zhang, Chunyu, Wang, Liping, He, Yang

“… We propose a computational framework called graph attention convolutional deep sparse autoencoder microbe-disease association (GCDSAEMDA…”
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Reciprocating compressor health monitoring based on BSInformer with deep convolutional AutoEncoder Autor Tian, Huixin, Ju, Bingtian, Feng, Shulin

“…•The reconstructed noisy data distribution is more similar to the normal data distribution. A composite model combining deep convolutional autoencoder and balanced sparse sampling Informer (MCA-BSInformer…”
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Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis Autor Miao, Mengqi, Sun, Yuanhang, Yu, Jianbo

“… Hence, in this article, a new deep neural network (DNN), sparse representation convolutional autoencoder (SRCAE…”
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SCAE—Stacked Convolutional Autoencoder for Fault Diagnosis of a Hydraulic Piston Pump with Limited Data Samples Autor Eraliev, Oybek, Lee, Kwang-Hee, Lee, Chul-Hee

“… In this study, we propose a novel DL model based on a stacked convolutional autoencoder (SCAE) to address the challenge of limited data…”
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Multistage committees of deep feedforward convolutional sparse denoise autoencoder for object recognition Autor Shicao Luo, Yongsheng Ding, Kuangrong Hao

“… The network is trained layer-wise via denoise autoencoder (dA) with L-BFGS to optimize convolutional kernels and no backpropagation is used…”
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Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks Autor Antonio, Victor Andrew A., Ono, Naoaki, Saito, Akira, Sato, Tetsuo, Altaf-Ul-Amin, Md, Kanaya, Shigehiko

“… A sparse deep autoencoder which minimizes local information entropy on the encoding layer is then proposed…”
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Multi-frequency and multi-domain human activity recognition based on SFCW radar using deep learning Autor Jia, Yong, Guo, Yong, Wang, Gang, Song, Ruiyuan, Cui, Guolong, Zhong, Xiaoling

“…Deep learning and radar make it feasible to automatically recognize human activities in various lighting conditions, even occlusion case, which significantly promotes the application of activity…”
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Attention-enhanced residual autoencoder for NIR spectral feature extraction and classification of grain varieties Autor Kabiso, Abel Chernet, Ko, Cheng-Hao

“… We propose SpecFuseNet, an attention-enhanced residual autoencoder, as a lightweight deep learning model for extracting NIR spectral features and classifying grain varieties…”
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A hybrid deep neural network based prediction of 300 MW coal-fired boiler combustion operation condition Autor Han, ZheZhe, Huang, YiZhi, Li, Jian, Zhang, Biao, Hossain, Md. Moinul, Xu, ChuanLong

“… To overcome these limitations, a novel prediction method for the combustion operation condition based on flame imaging and a hybrid deep neural network is proposed…”
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A deep learning framework with hybrid stacked sparse autoencoder for type 2 diabetes prediction Autor Abdussamad, Daud, Hanita, Sokkalingam, Rajalingam, Zubair, Muhammad, Khan, Iliyas Karim, Mahmood, Zafar

“… To overcome this challenge, this study introduces a deep learning-based algorithm, Hybrid Stacked Sparse Autoencoder (HSSAE…”
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Image Classification Based on Convolutional Denoising Sparse Autoencoder Autor Yu, Jianjiang, Qian, Subin, Zeng, Xiaoqin, Liu, Huiyi, Chen, Shuangshuang, Guo, Wei

“… In this paper, an unsupervised feature learning approach called convolutional denoising sparse autoencoder (CDSAE…”
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