Search Results - convolutional sparse autoencoder~

Sparse convolutional autoencoder‐based fault location for drive circuits in nuclear reactors by Yang, Cheng, Yuan, Yannan, Wang, Fu, Li, Jueying, Li, Ang, Min, Yuan, Zhang, Qiang

“…Drive circuit is a critical part of instrumentation and control systems in nuclear reactors, and its performance directly influences the operation of nuclear…”
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Convolutional Sparse Autoencoders for Image Classification by Luo, Wei, Li, Jun, Yang, Jian, Xu, Wei, Zhang, Jian

“…Convolutional sparse coding (CSC) can model local connections between image content and reduce the code redundancy when compared with patch-based sparse coding…”
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Detection and Classification of Transmission Line Faults Based on Unsupervised Feature Learning and Convolutional Sparse Autoencoder by Chen, Kunjin, Hu, Jun, He, Jinliang

“…We present in this paper a novel method for fault detection and classification in power transmission lines based on convolutional sparse autoencoder…”
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Self‐Attention‐Based Deep Convolutional Sparse Dense Autoencoder Model With Chebyshev‐Based Osprey Algorithm for Cardiovascular Disease Detection by 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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A novel multichannel sparse convolutional autoencoder for electrocardiogram signal compression by Bekiryazıcı, Tahir, Damkacı, Mehmet, Aydemir, Gürkan, Gürkan, Hakan

“… This paper presents a novel multichannel convolutional autoencoder model designed to compress ECG signals efficiently…”
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AI-based geological subsurface reconstruction using sparse convolutional autoencoders by Uribe-Ventura, Rodrigo, Barriga-Berrios, Yoan, Barriga-Gamarra, Jorge, Baby, Patrice, Viveen, Willem

“… This study presents an AI-based methodology using a sparse convolutional autoencoder for robust subsurface modeling under data constraints and integrating secondary data sources such as Vertical Electrical Sounding (VES) data…”
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Multi-resolution reconstruction of longitudinal streambed footprints using embedded sparse convolutional autoencoders by Yang, Yifan, Tang, Zihao, Shao, Dong, Xu, Zhonghou

“… This study introduces an embedded convolutional autoencoder (CAE) architecture designed for the multi-resolution reconstruction of longitudinal streambed footprints as sparse heatmaps…”
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XAI-DSCSA: explainable-AI-based deep semi-supervised convolutional sparse autoencoder for facial expression recognition by 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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Mineralized-Anomaly Identification Based on Convolutional Sparse Autoencoder Network and Isolated Forest by Yang, Na, Zhang, Zhenkai, Yang, Jianhua, Hong, Zenglin

“…-mineralization samples when they are utilized in mineralized-anomaly identification. This paper utilizes a convolutional sparse autoencoder network for realizing mineralized-anomaly identification…”
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Improving brain MRI denoising using convolutional AutoEncoder and sparse representations by Velayudham, A, Madhan Kumar, K., Krishna Priya, MS

“… However, noise often degrades image quality, leading to inaccurate diagnoses. To address this issue, a Convolutional AutoEncoder-based Orthogonal Matching Pursuit (CAE-OMP…”
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Feature extraction of fields of fluid dynamics data using sparse convolutional autoencoder by Obayashi, Wataru, Aono, Hikaru, Tatsukawa, Tomoaki, Fujii, Kozo

“… The technique here is based on the convolutional and sparse autoencoder learning algorithms and is called sparse convolutional autoencoder…”
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IoT and cloud computing-based automated epileptic seizure detection using optimized Siamese convolutional sparse autoencoder network by Ramkumar, M., Jamaesha, S. Syed, Gowtham, M. S., Kumar, C. Santhosh

“… This research work introduces a Siamese Convolutional Fire Hawk Sparse Autoencoder Network (SCFHSAN ) to detect different states of the epileptic seizures…”
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DSCAE: a denoising sparse convolutional autoencoder defense against adversarial examples by Ye, Hongwei, Liu, Xiaozhang, Li, Chunlai

“… In this work, we proposed a method called denoising sparse convolutional autoencoder (DSCAE) to defense against the adversarial perturbations…”
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Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis by 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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Aggregating Dual Attention Residual Network and Convolutional Sparse Autoencoder to Enhance the Diagnosis of Alzheimer's Disease by Jing, Shuiqing, Li, Ruohan, Mu, Shiguan, Shan, Shixiao, Li, Lanlan, Li, Jianlong, Sun, Yuan, Cui, Xinchun

“…) A convolutional sparse autoencoder, fortified with dual hidden strata, was devised to extract both global and spatial intelligence from PET images, thereby bolstering diagnostic efficacy; 3…”
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Sparse Convolutional Denoising Autoencoders for Genotype Imputation by 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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TumorAwareNet: Deep representation learning with attention based sparse convolutional denoising autoencoder for brain tumor recognition by 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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One-dimensional decoupled convolutional autoencoder with sparse self-attention mechanism for process monitoring by Yang, Yuguo, Shi, Hongbo, Song, Bing, Tao, Yang, Guo, Lei

“… decoupled convolutional autoencoder network with sparse self-attention mechanism under process knowledge constraints (PKC-SSAM-DCAE…”
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A stacked convolutional sparse denoising autoencoder model for underwater heterogeneous information data by Wang, Xingmei, Zhao, Yixu, Teng, Xuyang, Sun, Weiqi

“…•A novel stacked convolutional sparse denoising autoencoder (SCSDA) model is proposed.•The unrelated dataset was developed to simulate the underwater heterogeneous information data as the training set…”
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Hybrid twin attention based convolutional stacked sparse autoencoder for classification of defected weld images by Srikanth, T., Mani, M. Radhika

“…Welding is an essential joining process in industrial manufacturing. Many deep learning models are introduced to detect welding errors. However, with a…”
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