Search Results - "stacked autoencoder SAE"

Detection of sea‐surface target of coastal defense radar based on Stacked Autoencoder (SAE) algorithm by Yan, He, Chen, Chao, Jin, Guodong, Zhang, Jindong, Zhang, Gong, Zhu, Daiyin

“… In this study, a novel algorithm for sea‐surface target detection based on a stacked autoencoder (SAE…”
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Classification of autistic subjects employing modified volume local binary pattern (MVLBP) and stacked Autoencoder (SAE) on functional magnetic resonance imaging (fMRI) by M., Kaviya Elakkiya, Dejey

“…Autism Spectrum Disorder (ASD) or Autism is a developmental disorder that impairs the ability to communicate and interact. Screening of autism is strenuous…”
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A novel semi-supervised pre-training strategy for deep networks and its application for quality variable prediction in industrial processes by Yuan, Xiaofeng, Ou, Chen, Wang, Yalin, Yang, Chunhua, Gui, Weihua

“…•A semi-supervised autoencoder (SS-AE) is first developed as the basic network to extract quality-related features.•By hierarchically stacking multiple SS-AEs,…”
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Deep quality-related feature extraction for soft sensing modeling: A deep learning approach with hybrid VW-SAE by Yuan, Xiaofeng, Ou, Chen, Wang, Yalin, Yang, Chunhua, Gui, Weihua

“…Soft sensors have been extensively used to predict difficult-to-measure quality variables for effective modeling, control and optimization of industrial…”
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Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE by Yuan, Xiaofeng, Huang, Biao, Wang, Yalin, Yang, Chunhua, Gui, Weihua

“… Hence, deep stacked autoencoder (SAE) is introduced for soft sensor in this paper. As for output prediction purpose, traditional deep learning algorithms cannot extract high-level output-related features…”
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High-Voltage Circuit Breaker Fault Diagnosis Using a Hybrid Feature Transformation Approach Based on Random Forest and Stacked Autoencoder by Ma, Suliang, Chen, Mingxuan, Wu, Jianwen, Wang, Yuhao, Jia, Bowen, Jiang, Yuan

“…In recent years, machine learning techniques have been applied to test the fault type in high-voltage circuit breakers (HVCBs). Most related research involves…”
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Gated Stacked Target-Related Autoencoder: A Novel Deep Feature Extraction and Layerwise Ensemble Method for Industrial Soft Sensor Application by Sun, Qingqiang, Ge, Zhiqiang

“… In this work, deep stacked autoencoder (SAE) is introduced to construct a soft sensor model. Nevertheless, conventional SAE-based methods do not take information related…”
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Fusing stacked autoencoder and long short-term memory for regional multistep-ahead flood inundation forecasts by Kao, I-Feng, Liou, Jia-Yi, Lee, Meng-Hsin, Chang, Fi-John

“…•Use Stacked Autoencoder (SAE) to reduce the dimension of regional inundation data…”
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A Novel Double-Stacked Autoencoder for Power Transformers DGA Signals With An Imbalanced Data Structure by Yang, Dongsheng, Qin, Jia, Pang, Yongheng, Huang, Tingwen

“…Artificial intelligence is the general trend in the field of power equipment fault diagnosis. However, limited by operation characteristics and data defects,…”
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Deep Learning-Based Classification of Hyperspectral Data by Chen, Yushi, Lin, Zhouhan, Zhao, Xing, Wang, Gang, Gu, Yanfeng

“…Classification is one of the most popular topics in hyperspectral remote sensing. In the last two decades, a huge number of methods were proposed to deal with…”
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Kernel-Based Multilayer Extreme Learning Machines for Representation Learning by Wong, Chi Man, Vong, Chi Man, Wong, Pak Kin, Cao, Jiuwen

“…Recently, multilayer extreme learning machine (ML-ELM) was applied to stacked autoencoder (SAE…”
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Deep Learning for Industrial KPI Prediction: When Ensemble Learning Meets Semi-Supervised Data by Sun, Qingqiang, Ge, Zhiqiang

“…Soft-sensing techniques are of great significance in industrial processes for monitoring and prediction of key performance indicators. Due to the effectiveness…”
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Processes soft modeling based on stacked autoencoders and wavelet extreme learning machine for aluminum plant-wide application by Lei, Yongxiang, Karimi, Hamid Reza, Cen, Lihui, Chen, Xiaofang, Xie, Yongfang

“… First, a stacked autoencoder (SAE) is used to extract the deep features. Then, a top-layer extreme learning machine (ELM…”
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Stacked Fisher autoencoder for SAR change detection by Liu, Ganchao, Li, Lingling, Jiao, Licheng, Dong, Yongsheng, Li, Xuelong

“…•The original SAE is expanded to suit with the multiplicative noise in SAR change detection.•The features extracted by SFAE are more discriminative than the…”
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Stacked maximal quality-driven autoencoder: Deep feature representation for soft analyzer and its application on industrial processes by Chen, Junming, Fan, Shaosheng, Yang, Chunhua, Zhou, Can, Zhu, Hongqiu, Li, Yonggang

“…Deep learning based soft analyzers are important for modern industrial process monitoring and measurement, which aim to establish prediction models between…”
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Rotor-Current-Based Fault Diagnosis for DFIG Wind Turbine Drivetrain Gearboxes Using Frequency Analysis and a Deep Classifier by Cheng, Fangzhou, Wang, Jun, Qu, Liyan, Qiao, Wei

“…Fault diagnosis of drivetrain gearboxes is a prominent challenge in wind turbine condition monitoring. Many machine learning algorithms have been applied to…”
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Visualization of defects in CFRP-reinforced steel structures using improved eddy current pulsed thermography by Xie, Jing, Xu, Changhang, Wu, Changwei, Gao, Lemei, Chen, Guoming, Li, Guozhen, Song, Gangbing

“… In this study, eddy current pulsed thermography (ECPT) was exploited to inductively heat the inspected structures and a stacked autoencoder (SAE…”
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Quality-driven deep feature representation learning and its industrial application to soft sensors by Song, Xiao-Lu, Zhang, Ning, Shi, Yilin, He, Yan-Lin, Xu, Yuan, Zhu, Qun-Xiong

“… Stacked AutoEncoder (SAE) is able to capture the intricate structures of data characterized by high dimensionality and strong non-linearity by extracting abstract features layer by layer, making it widely used…”
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Adaptive cascade enhancement broad learning system combined with stacked correlation information autoencoder for soft sensor modeling of industrial process by Ni, Mingming, Li, Shaojun

“…•A new feature extraction method which introduces the correlation coefficient and the dominant variable into the stacked autoencoder has been developed.•An…”
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Rock mass quality classification based on deep learning: A feasibility study for stacked autoencoders by Sheng, Danjie, Yu, Jin, Tan, Fei, Tong, Defu, Yan, Tianjun, Lv, Jiahe

“… To develop a tool that can deliver quick and accurate evaluation of rock mass quality, a deep learning approach is developed, which uses stacked autoencoders (SAEs…”
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