Výsledky vyhledávání - stacked sparse autoencoder(SSAE)~

SSAE‐MLP: Stacked sparse autoencoders‐based multi‐layer perceptron for main bearing temperature prediction of large‐scale wind turbines Autor Xiao, Xiaocong, Liu, Jianxun, Liu, Deshun, Tang, Yufei, Dai, Juchuan, Zhang, Fan

“… To achieve the goal, this paper proposes a novel deep learning approach named stacked sparse autoencoder multi‐layer perceptron (SSAE‐MLP…”
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Novel Pelican Optimization Algorithm (POA) With Stacked Sparse Autoencoder (SSAE) Based IDS for Network Security Autor Kanimozhi, R., Neela Madheswari, A.

“… The proposed IDS, also termed as the POA‐SSAE IDS model (pelican optimization model‐stacked…”
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Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images Autor Jun Xu, Lei Xiang, Qingshan Liu, Gilmore, Hannah, Jianzhong Wu, Jinghai Tang, Madabhushi, Anant

“…Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of…”
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Improved Human Activity Recognition Using Stacked Sparse Autoencoder (SSAE) Algorithm Autor Aziz, Firman, Mustamin, Nurul Fathanah, Rijal, Muhammad, Tanniewa, Adam M

“…This study aims to enhance the performance of Human Activity Recognition (HAR) systems by implementing the Stacked Sparse Autoencoder (SSAE…”
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SSAE‐KPLS: A quality‐related process monitoring via integrating stacked sparse autoencoder with kernel partial least squares Autor Ye, Zhenyu, Wu, Ping, He, Yuchen, Pan, Haipeng

“…‐related process monitoring method via integrating stacked sparse autoencoder (SSAE) with KPLS (SSAE‐KPLS). First, an SSAE model is employed to exploit the nonlinearity within process variables…”
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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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Stacked Sparse Autoencoder (SSAE) based framework for nuclei patch classification on breast cancer histopathology Autor Jun Xu, Lei Xiang, Renlong Hang, Jianzhong Wu

“…In this paper, a Stacked Sparse Autoencoder (SSAE) based framework is presented for nuclei classification on breast cancer histopathology…”
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Unsupervised Spectral-Spatial Feature Learning With Stacked Sparse Autoencoder for Hyperspectral Imagery Classification Autor Tao, Chao, Pan, Hongbo, Li, Yansheng, Zou, Zhengrou

“… This is achieved by learning a feature mapping function based on stacked sparse autoencoder. Considering that hyperspectral imagery (HSI…”
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Stacked Sparse Autoencoder in PolSAR Data Classification Using Local Spatial Information Autor Zhang, Lu, Ma, Wenping, Zhang, Dan

“… Among various classification techniques, the stacked sparse autoencoder (SSAE) is a kind of deep learning method that can automatically learn useful features layer by layer in an unsupervised manner…”
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Road and Sight Functions Detection and Recognition Using Stacked Sparse AutoEncoders (SSAE) Autor Kalaiselvi, T C, Swathi, S

“…The main objective of the paper is to detect and recognize the traffic sign using deep learning model using Stacked Sparse AutoEncoders (SSAE…”
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Nonlinear Generalized Predictive Control of the Crystal Diameter in CZ-Si Crystal Growth Process Based on Stacked Sparse Autoencoder Autor Liu, Ding, Zhang, Ni, Jiang, Lei, Zhao, Xiao-Guo, Duan, Wei-Feng

“… predictive controller (GPC) based on the stacked sparse autoencoder (SSAE) is proposed under the new control structure…”
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Discriminative Feature Learning With Distance Constrained Stacked Sparse Autoencoder for Hyperspectral Target Detection Autor Shi, Yanzi, Lei, Jie, Yin, Yaping, Cao, Kailang, Li, Yunsong, Chang, Chein-I

“… Unlike supervised networks, unsupervised stacked sparse autoencoders (SSAEs) can learn deep and nonlinear features without any labeled data…”
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Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample Autor Saufi, Syahril Ramadhan, Ahmad, Zair Asrar Bin, Leong, Mohd Salman, Lim, Meng Hee

“… To compensate for this deficiency, a DL model based on a stacked sparse autoencoder (SSAE) model is designed to deal with limited sample data…”
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Fusing Heterogeneous Features From Stacked Sparse Autoencoder for Histopathological Image Analysis Autor Zhang, Xiaofan, Dou, Hang, Ju, Tao, Xu, Jun, Zhang, Shaoting

“… from the cell detection results by a stacked sparse autoencoder. Because of the dramatically different characteristics and representations of these heterogeneous features (i.e…”
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Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning Autor Sun, Jiedi, Yan, Changhong, Wen, Jiangtao

“…Effective intelligent fault diagnosis has long been a research focus on the condition monitoring of rotary machinery systems. Traditionally, time-domain…”
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Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model for Hyperspectral Image Classification Autor Deng, Cheng, Xue, Yumeng, Liu, Xianglong, Li, Chao, Tao, Dacheng

“… More specifically, deep joint spectral-spatial feature is first extracted through hierarchical stacked sparse autoencoder (SSAE) networks…”
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A denoising method for ECG signals based on CEEMDAN-TSO and stacked sparse autoencoders Autor Li, Shun, Li, Juan, Mao, Jiandong, Hong, Wei, Sun, Ao

“…), Tuna Swarm Optimization (TSO), and Stacked Sparse Autoencoder (SSAE), named CEEMDAN-TSO-SSAE…”
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Abnormal Dynamic Recognition of Space Targets from ISAR Image Sequences with SSAE-LSTM Network Autor Duan, Jia, Ma, Yan, Zhang, Lei, Xie, Pengfei

“… With the accommodation of the stacked sparse autoencoder (SSAE) network joint sparsity constraint, the geometrical feature flow of an ISAR image sequence is learned to represent the target dynamics concisely…”
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A Sleep Apnea Detection Method Based on Unsupervised Feature Learning and Single-Lead Electrocardiogram Autor Feng, Kaicheng, Qin, Hengji, Wu, Shan, Pan, Weifeng, Liu, Guanzheng

“… In this study, an SA detection model based on frequential stacked sparse auto-encoder (FSSAE) and time-dependent cost-sensitive (TDCS…”
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Diagnosis of Interturn Short-Circuit Faults in Permanent Magnet Synchronous Motors Based on Few-Shot Learning Under a Federated Learning Framework Autor Zhang, Jinglin, Wang, Yanbo, Zhu, Kai, Zhang, Yi, Li, Yuanjiang

“… Its global model is updated by the local client without sharing data at each round. Considering computing resources and communication loss of multiple clients, an efficient method based on stacked sparse autoencoders (SSAEs…”
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