Výsledky vyhledávání - "Supervised autoencoder"

Novel Stacked Input-Enhanced Supervised Autoencoder Integrated With Gated Recurrent Unit for Soft Sensing Autor Tian, Ye, Xu, Yuan, Zhu, Qun-Xiong, He, Yan-Lin

“…Machine learning techniques have been successfully utilized as effective soft sensing for industrial processes. Unfortunately, as modern industrial processes…”
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Discriminant autoencoder for feature extraction in fault diagnosis Autor Luo, Xiaoyi, Li, Xianmin, Wang, Ziyang, Liang, Jun

“…Nowadays, some traditional autoencoders and their extensions have been widely applied in data-driven fault diagnosis for feature extraction. However, because…”
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Enhanced Financial Fraud Detection via SISAE‐METADES: A Supervised Deep Representation and Dynamic Ensemble Approach Autor Wang, Chang, Fang, Sheng, Zhao, Fangsu, Mu, Zongmei

“…Detecting financial reporting fraud is vital for preserving market integrity and protecting investors from substantial losses. Yet, the challenges of high…”
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A personalized classification model using similarity learning via supervised autoencoder Autor Jo, Hyunjae, Jun, Chi-Hyuck

“…Personalized modellingmodelingusually trains a predictive model for a new point using only observations similar to the new point. However, existing…”
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scSSA: A clustering method for single cell RNA-seq data based on semi-supervised autoencoder Autor Zhao, Jian-Ping, Hou, Tong-Shuai, Su, Yansen, Zheng, Chun-Hou

“…•In this study, We proposed to use semi-supervised autoencoder to reduce the dimension of data, because it makes good use of some existing label…”
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Dual‐noise autoencoder combining pseudo‐labels and consistency regularization for process fault classification Autor Guo, Xiaoping, Guo, Qingyu, Li, Yuan

“…In the classification of industrial process faults, the collected process fault data has the problem of having more irrelevant fault information, limited…”
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Group sparse autoencoder Autor Sankaran, Anush, Vatsa, Mayank, Singh, Richa, Majumdar, Angshul

“…Unsupervised feature extraction is gaining a lot of research attention following its success to represent any kind of noisy data. Owing to the presence of a…”
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Just-in-time updating soft sensor model of endpoint carbon content and temperature in BOF steelmaking based on deep residual supervised autoencoder Autor Yang, Lu, Liu, Hui, Chen, Fugang

“…The key of Basic oxygen furnace (BOF) endpoint control is to achieve accurate forecast of the endpoint carbon content and temperature. Due to the highly…”
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Synthetic Lung Ultrasound Data Generation Using Autoencoder With Generative Adversarial Network Autor Fatima, Noreen, Mento, Federico, Afrakhteh, Sajjad, Perrone, Tiziano, Smargiassi, Andrea, Inchingolo, Riccardo, Demi, Libertario

“…Class imbalance is a significant challenge in medical image analysis, particularly in lung ultrasound (LUS), where severe patterns are often underrepresented…”
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Semi-Supervised Autoencoder for Chemical Gas Classification with FTIR Spectrum Autor Jang, Hee-Deok, Kwon, Seokjoon, Nam, Hyunwoo, Chang, Dong Eui

“…Chemical warfare agents pose a serious threat due to their extreme toxicity, necessitating swift the identification of chemical gases and individual responses…”
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Ironmaking process modeling uncertainty quantification via conformal prediction based on random vector functional link networks Autor Zhou, Ping, Wen, Chaoyao, Zhao, Peng, Li, Mingjie

“…For real-world industrial system modeling, dynamic stochastic errors inevitably exist in data-driven deterministic predictions (i.e., point predictions). The…”
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Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images Autor Cheng, Jianhong, Zhao, Wei, Liu, Jin, Xie, Xingzhi, Wu, Shangjie, Liu, Liangliang, Yue, Hailin, Li, Junjian, Wang, Jianxin, Liu, Jun

“…Accurate and rapid diagnosis of coronavirus disease 2019 (COVID-19) from chest CT scans is of great importance and urgency during the worldwide outbreak…”
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Morphological Autoencoders for Beat-by-Beat Atrial Fibrillation Detection Using Single-Lead ECG Autor Silva, Rafael, Fred, Ana, Plácido da Silva, Hugo

“…Engineered feature extraction can compromise the ability of Atrial Fibrillation (AFib) detection algorithms to deliver near real-time results. Autoencoders…”
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Semi-supervised denoising autoencoder with multiple consistency regularization for process fault classification Autor Guo, Xiaoping, Guo, Qingyu, Li, Yuan

“…Process fault classification constitutes a critical component for ensuring efficient and stable industrial operations. If the collected process data is…”
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Are you eligible? Predicting adulthood from face images via Class Specific Mean Autoencoder Autor Singh, Maneet, Nagpal, Shruti, Vatsa, Mayank, Singh, Richa

“…•Proposed Class Specific Mean Autoencoder for learning class representative features.•Designed an efficient algorithm for adulthood classification based on…”
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Captured multi-label relations via joint deep supervised autoencoder Autor Lian, Si-ming, Liu, Jian-wei, Lu, Run-kun, Luo, Xiong-lin

“…The mapping relations learning between instances and multiple labels should reflect the underlying joint probability distribution following by the data sets…”
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Auto-Encoders Derivatives on Different Occluded Face Images: Comprehensive Review and New Results Autor Masoudi, Azin, Ahmadi, Majid

“…This paper presents a novel approach for improving occluded face recognition performance using a family of autoencoders (AE) architectures. The proposed…”
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Convolutional autoencoder for on-demand parametric inverse design of local resonator geometry in wind turbine metastructure targeting vibration control Autor Naeini, Mohammadreza Sahaf, Machado, Marcela, Dutkiewicz, Maciej

“…Vibration control in structures is essential to mitigate undesired dynamic responses, thereby enhancing stability, safety, and performance under varying…”
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Stacked semi-supervised autoencoder-regularized RVFLNs for reliable prediction of molten iron quality in blast furnace Autor Zhou, Ping, Zhao, Peng, Ou, Zihui, Chai, Tianyou

“…This paper proposes a novel stacked semi-supervised autoencoder-regularized random vector functional-link networks (RVFLNs) for reliable prediction of molten…”
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A Semi-Supervised Autoencoder With an Auxiliary Task (SAAT) for Power Transformer Fault Diagnosis Using Dissolved Gas Analysis Autor Kim, Sunuwe, Jo, Soo-Ho, Kim, Wongon, Park, Jongmin, Jeong, Jingyo, Han, Yeongmin, Kim, Daeil, Youn, Byeng Dong

“…This paper proposes a semi-supervised autoencoder with an auxiliary task (SAAT) to extract a health feature space for power transformer fault diagnosis using…”
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