Search Results - Autoencoder (AE) models

DOT-AE-GAN: a hybrid autoencoder–GAN model for enhanced ultrasound-guided diffuse optical tomography reconstruction by Hossain, Md. Iqbal, Xue, Minghao, Wang, Lukai, Zhu, Quing

“… We introduce a hybrid machine learning model that combines the strengths of autoencoders (AEs) and generative adversarial networks…”
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Predicting Channel Delay State Information in 5G-TSN Systems Using Extreme Learning Machine Autoencoder (ELM-AE) Model Based on Intelligent Deep Extreme Learning Machine (DELM) by Zhang, Chaoyi, Wang, Jianquan, Fu, Meixia

“… This serves as a data foundation for subsequent intelligent prediction. Next, to make better use of the local information of channel state and achieve fast convergence, we employ an extreme learning machine autoencoder (ELM-AE…”
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AE-DTNN: Autoencoder–Dense–Transformer Neural Network Model for Efficient Anomaly-Based Intrusion Detection Systems by Kamal, Hesham, Mashaly, Maggie

“…In this study, we introduce an enhanced hybrid Autoencoder–Dense–Transformer Neural Network (AE-DTNN…”
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End-to-end deep learning for smart maritime threat detection: an AE–CNN–LSTM-based approach by Anuja, R., Annrose, J.

“… To improve detection fidelity under these conditions, we present a hybrid Autoencoder–Convolutional Neural Network…”
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Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin by Han, Chengjia, Wang, Zixin, Fu, Yuguang, Dyke, Shirley, Shahriar, Adnan

“… numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model…”
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AE-BPNN: autoencoder and backpropagation neural network-based model for lithium-ion battery state of health estimation by Al-Dulaimi, Abdullah Ahmed, Guneser, Muhammet Tahir, Al-Shabandar, Raghad, Gu, Yeonghyeon, Syafrudin, Muhammad, Fitriyani, Norma Latif

“… An autoencoder backpropagation neural network (AE-BPNN) was developed for unsupervised processing, dimensionality reduction, feature extraction, and SOH estimation…”
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LLM-AE-MP: Web Attack Detection Using a Large Language Model with Autoencoder and Multilayer Perceptron by Yang, Jing, Wu, Yuangui, Yuan, Yuping, Xue, Haozhong, Bourouis, Sami, Abdel-Salam, Mahmoud, Prajapat, Sunil, Por, Lip Yee

“…) requests using an autoencoder (AE). The integration of AE allows for efficient feature distillation, enhancing the sensitivity of the model to anomalies in HTTP traffic…”
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Research on a Novel Unsupervised-Learning-Based Pipeline Leak Detection Method Based on Temporal Kolmogorov–Arnold Network with Autoencoder Integration by Wu, Hengyu, Jiang, Zhu, Zhang, Xiang, Cheng, Jian

“… The proposed model combines the Kolmogorov–Arnold Network (KAN) with an autoencoder (AE). This model combines the Kolmogorov–Arnold Network (KAN…”
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Adaptive Two-Stage Multisensor Convolutional Autoencoder Model for Lossy Compression of Hyperspectral Data by Kuester, Jannick, Gross, Wolfgang, Schreiner, Simon, Middelmann, Wolfgang, Heizmann, Michael

“… This work addresses the challenge of transferability of autoencoder (AE) models for lossy compression of spatially independent and unknown hyperspectral datasets acquired from different sensor platforms…”
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Adversarial deconfounding autoencoder for learning robust gene expression embeddings by Dincer, Ayse B, Janizek, Joseph D, Lee, Su-In

“…Abstract Motivation Increasing number of gene expression profiles has enabled the use of complex models, such as deep unsupervised neural networks, to extract a latent space from these profiles…”
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Multi-view-AE: A Python package for multi-view autoencoder models by Aguila, Ana Lawry, Jayme, Alejandra, Montaña-Brown, Nina, Heuveline, Vincent, Altmann, Andre

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Dictionary trained attention constrained low rank and sparse autoencoder for hyperspectral anomaly detection by Hu, Xing, Li, Zhixuan, Luo, Lingkun, Karimi, Hamid Reza, Zhang, Dawei

“… Dictionary representations and deep learning Autoencoder (AE) models have proven effective in hyperspectral anomaly detection…”
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Exploring Autoencoder-based Error-bounded Compression for Scientific Data by Liu, Jinyang, Di, Sheng, Zhao, Kai, Jin, Sian, Tao, Dingwen, Liang, Xin, Chen, Zizhong, Cappello, Franck

“… Not only can it significantly reduce data size, but it also can control the compression errors based on user-specified error bounds. Autoencoder (AE…”
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Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model by Su, Lingtao, Xu, Chunhui, Zeng, Shuai, Su, Li, Joshi, Trupti, Stacey, Gary, Xu, Dong

“…) model to map gene expressions into a latent space and adapted a standard unsupervised autoencoder (AE…”
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scDAC: deep adaptive clustering of single-cell transcriptomic data with coupled autoencoder and Dirichlet process mixture model by An, Sijing, Shi, Jinhui, Liu, Runyan, Chen, Yaowen, Wang, Jing, Hu, Shuofeng, Xia, Xinyu, Dong, Guohua, Bo, Xiaochen, He, Zhen, Ying, Xiaomin

“… Results Here, we propose a single-cell Deep Adaptive Clustering (scDAC) model by coupling the Autoencoder (AE…”
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Towards Efficient Electricity Forecasting in Residential and Commercial Buildings: A Novel Hybrid CNN with a LSTM-AE based Framework by Khan, Zulfiqar, Hussain, Tanveer, Ullah, Amin, Rho, Seungmin, Lee, Miyoung, Baik, Sung

“…) with an long short-term memory autoencoder (LSTM-AE) model for future energy prediction in residential and commercial buildings…”
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LSTM-based autoencoder models for real-time quality control of wastewater treatment sensor data by Seshan, Siddharth, Vries, Dirk, Immink, Jasper, van der Helm, Alex, Poinapen, Johann

“… long short-term memory (LSTM) autoencoder (AE) models, to reconcile faulty sensor signals in WWTPs as compared to autoregressive integrated moving average (ARIMA) models…”
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Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models by Melo, Renato, Finotti, Rafaelle, Guedes, António, Gonçalves, Vítor, Meixedo, Andreia, Ribeiro, Diogo, Barbosa, Flávio, Cury, Alexandre

“…This study presents a comparative analysis of three AutoEncoder (AE) models—Variational AutoEncoder (VAE…”
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Comparative Study on Three Autoencoder‐Based Deep Learning Algorithms for Geochemical Anomaly Identification by Feng, Bin, Chen, Lirong, Xu, Yongyang, Zhang, Yu

“…‐Ag metallogenic area in southwest Fujian province as samples. Three unsupervised deep learning models: the autoencoder (AE), multi…”
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Research on residual attention-based mechanism autoencoder for microseismic denoising network model by Li, Jiaming, Tang, Beichang, Zhang, Shuguang, Tang, Shibin, Qiu, Hongting, Huang, Xiang, Liu, Wenbo

“…•A residual attention-based mechanism autoencoder for microseismic denoising network model is proposed…”
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