Výsledky vyhľadávania - "Sparse stacked autoencoder"

Cervical cancer classification using sparse stacked autoencoder and fuzzy ARTMAP Autor Liaw, Lawrence Chuin Ming, Tan, Shing Chiang, Goh, Pey Yun, Lim, Chee Peng

“… sparse stacked autoencoder (SSAE) and fuzzy adaptive resonance theory MAP (FAM), respectively, and is denoted as SSAE-FAM…”
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Fault classification based on variable‐weighted dynamic sparse stacked autoencoder for industrial processes Autor Dong, Jie, Tu, Yanan, Peng, Kaixiang

“… In this paper, a fault classification method based on a variable‐weighted dynamic sparse stacked autoencoder is proposed…”
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Sparse stacked autoencoder network for complex system monitoring with industrial applications Autor Deng, Ziwei, Li, Yuxuan, Zhu, Hongqiu, Huang, Keke, Tang, Zhaohui, Wang, Zhen

“…•A fault classification and isolation method based on SAE is proposed for complex system.•Deep learning model formed by AE with sparse and regular constraints…”
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Novel semi-supervised sparse stacked autoencoder integrated with local linear embedding for industrial soft sensing Autor He, Yan-Lin, Jiang, Yu, Gao, Hui-Hui, Xu, Yuan, Zhu, Qun-Xiong

“…, posing significant challenges for soft sensing. To address these issues, this paper proposes novel Semi-Supervised Sparse Stacked Autoencoder integrated with the Local Linear Embedding algorithm (SS-SAE-LLE…”
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Improved Diagnostic Approach for BRB Detection and Classification in Inverter-Driven Induction Motors Employing Sparse Stacked Autoencoder (SSAE) and LightGBM Autor Khan, Muhammad Amir, Asad, Bilal, Vaimann, Toomas, Kallaste, Ants

“…This study introduces an innovative approach to diagnostics, employing a unique combination of techniques including a stratified group K-fold cross-validation method and a sparse stacked autoencoder (SSAE) alongside LightGBM…”
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Hybrid Feature Embedded Sparse Stacked Autoencoder and Manifold Dimensionality Reduction Ensemble for Mental Health Speech Recognition Autor Chen, Hong, Lin, Yuan, Li, Yongming, Wang, Wei, Wang, Pin, Lei, Yan

“… This paper proposes an embedded hybrid feature deep sparse stacked autoencoder ensemble method to solve this problem…”
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Psychosis speech recognition algorithm based on deep embedded sparse stacked autoencoder and manifold ensemble Autor Zhang, Yi, Qin, Xiaolin, Lin, Yuan, Li, Yongming, Wang, Pin, Zhang, Zuwei, Li, Xiaofei

“…Speech feature learning is the core and key of speech recognition method for mental illness. Deep feature learning can automatically extract speech features,…”
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Dynamic time warping optimization-based non-intrusive load monitoring for multiple household appliances Autor Li, Menghui, Tu, Zhaoyu, Wang, Jun, Xu, Peihua, Wang, Xianbo

“…Non invasive load monitoring (NILM) is beneficial for enhancing the monitoring capability of the distribution network and is crucial for improving the safety…”
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Long-Distance Pipeline Safety Early Warning: A Distributed Optical Fiber Sensing Semi-Supervised Learning Method Autor Yang, Yiyuan, Zhang, Haifeng, Li, Yi

“… Concretely, the sparse stacked autoencoder trained…”
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Ensemble of deep learning and IoT technologies for improved safety in smart indoor activity monitoring for visually impaired individuals Autor Al Duhayyim, Mesfer

“…Old and vision-impaired indoor action monitoring utilizes sensor technology to observe movement and interaction in the living area. This model can recognize…”
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Snapshot High Dynamic Range Imaging via Sparse Representations and Feature Learning Autor Fotiadou, Konstantina, Tsagkatakis, Grigorios, Tsakalides, Panagiotis

“…Bracketed High Dynamic Range (HDR) imaging architectures acquire a sequence of Low Dynamic Range (LDR) images in order to either produce a HDR image or an…”
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A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis Autor Sohaib, Muhammad, Kim, Cheol-Hong, Kim, Jong-Myon

“… A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE)-based deep neural networks (DNNs…”
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Proactive Critical Energy Infrastructure Protection via Deep Feature Learning Autor Fotiadou, Konstantina, Velivassaki, Terpsichori Helen, Voulkidis, Artemis, Skias, Dimitrios, De Santis, Corrado, Zahariadis, Theodore

“…Autonomous fault detection plays a major role in the Critical Energy Infrastructure (CEI) domain, since sensor faults cause irreparable damage and lead to…”
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STEP-compliant CNC system featuring real-time material removal simulation for online tool wear monitoring Autor Qiu, Tianze, Liu, Yan, Xiao, Wenlei, Zhao, Gang, Liu, Qiang

“… Second, a sparse stacked autoencoder extracts and compresses…”
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Autoencoder-aided measurement of concentration from a single line of speckle Autor Karamehmedović, Mirza, Šehić, Kenan, Dammann, Bernd, Suljagić, Mirza, Karamehmedović, Emir

“… (linear principal component analysis, support vector machine (SVM)) and a neural network, in the form of a sparse stacked autoencoder (SSAE…”
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A Semi-Supervised Stacked Autoencoder Using the Pseudo Label for Classification Tasks Autor Lai, Jie, Wang, Xiaodan, Xiang, Qian, Quan, Wen, Song, Yafei

“…The efficiency and cognitive limitations of manual sample labeling result in a large number of unlabeled training samples in practical applications. Making…”
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Unsupervised Deep Learning CAD Scheme for the Detection of Malaria in Blood Smear Microscopic Images Autor Pattanaik, Priyadarshini Adyasha, Mittal, Mohit, Khan, Mohammad Zubair

“… The parameters of the scheme are pre-trained by functional link artificial neural network followed by sparse stacked autoencoder…”
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Discriminative Autoencoder for Feature Extraction: Application to Character Recognition Autor Gogna, Anupriya, Majumdar, Angshul

“…Conventionally, autoencoders are unsupervised representation learning tools. In this work, we propose a novel discriminative autoencoder. Use of supervised…”
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Identification of Anomalies in Lung and Colon Cancer Using Computer Vision-Based Swin Transformer with Ensemble Model on Histopathological Images Autor Alsulami, Abdulkream A., Albarakati, Aishah, AL-Ghamdi, Abdullah AL-Malaise, Ragab, Mahmoud

“…Lung and colon cancer (LCC) is a dominant life-threatening disease that needs timely attention and precise diagnosis for efficient treatment. The conventional…”
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GRU‐based stacked sparse autoencoder with attention mechanism for process monitoring Autor Miao, Zengdi, Wu, Ping, Wu, Zhenquan, Jia, Xiangjun, Xu, Hui, Jiang, Jian

“…) model is developed for process monitoring. This model leverages the power of recurrent neural networks in conjunction with the sparse stacked autoencoder to tackle the temporal and nonlinear features present in process data…”
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