Search Results - stacked denoising autoencoder(sae)

Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label by Xu, Fan, Tse, Wai tai Peter, Tse, Yiu Lun

“…Most deep learning models such as stacked autoencoder (SAE) and stacked denoising autoencoder (SDAE…”
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Constructing a health indicator for bearing degradation assessment via an unsupervised and enhanced stacked autoencoder by Xu, Fan, Wang, Lei

“… To demonstrate our proposed method is better than other models, including the stacked autoencoder (SAE…”
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Object-Based Land-Cover Supervised Classification for Very-High-Resolution UAV Images Using Stacked Denoising Autoencoders by Zhang, Xiaodong, Chen, Guanzhou, Wang, Wenbo, Wang, Qing, Dai, Fan

“… Second, we extract the spectral, spatial, and texture features for each object. Then we put all features into stacked autoencoders (SAE…”
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Building feature space of extreme learning machine with sparse denoising stacked-autoencoder by Cao, Le-le, Huang, Wen-bing, Sun, Fu-chun

“… Deep learning algorithms such as stacked autoencoder (SAE) and deep belief network (DBN) are built on learning several levels of representation of the input…”
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HCC Recognition Within Ultrasound Images Employing Advanced Textural Features with Deep Learning Techniques by Mitrea, Delia, Nedevschi, Sergiu, Mitrea, Paulina, Lupsor, Monica Platon, Badea, Radu

“… Regarding the deep learning methods, we focus on Stacked Denoising Autoencoders (SAE), so we study its impact upon the performance of HCC computerized diagnosis…”
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Deep learning algorithms for brain disease detection with magnetic induction tomography by Chen, Ruijuan, Huang, Juan, Song, Yixiang, Li, Bingnan, Wang, Jinhai, Wang, Huiquan

“…), stacked autoencoder (SAE), and denoising autoencoder (DAE), are used to solve the nonlinear reconstruction problem of MIT, and the reconstruction results of DL networks and back…”
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Fault Diagnosis of Rolling Bearing Based on Multiscale Intrinsic Mode Function Permutation Entropy and a Stacked Sparse Denoising Autoencoder by Dai, Juying, Tang, Jian, Shao, Faming, Huang, Shuzhan, Wang, Yangyang

“… To realize representative features mining and automatic recognition of bearing health condition, a diagnostic model of stacked sparse denoising autoencoder (SSDAE…”
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Denoising magnetic resonance spectroscopy (MRS) data using stacked autoencoder for improving signal‐to‐noise ratio and speed of MRS by Wang, Jing, Ji, Bing, Lei, Yang, Liu, Tian, Mao, Hui, Yang, Xiaofeng

“…Background While magnetic resonance imaging (MRI) provides high resolution anatomical images with sharp soft tissue contrast, magnetic resonance spectroscopy…”
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Denoised Bottleneck Features From Deep Autoencoders for Telephone Conversation Analysis by Janod, Killian, Morchid, Mohamed, Dufour, Richard, Linares, Georges, De Mori, Renato

“… Recently, denoisng autoencoders (DAE) and stacked autoencoders (SAE) have been proposed with interesting results for acoustic feature denoising tasks…”
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Rough Deep Neural Architecture for Short-Term Wind Speed Forecasting by Khodayar, Mahdi, Kaynak, Okyay, Khodayar, Mohammad E.

“…) architecture with stacked autoencoder (SAE) and stacked denoising autoencoder (SDAE) for ultrashort-term and short-term wind speed forecasting. Autoencoders (AEs…”
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Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques by Mitrea, Delia-Alexandrina, Brehar, Raluca, Nedevschi, Sergiu, Lupsor-Platon, Monica, Socaciu, Mihai, Badea, Radu

“…) and Stacked Denoising Autoencoders (SAE), were involved in our research. The best accuracy of 91…”
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A sparse stacked denoising autoencoder with optimized transfer learning applied to the fault diagnosis of rolling bearings by Sun, Meidi, Wang, Hui, Liu, Ping, Huang, Shoudao, Fan, Peng

“… As an unsupervised deep learning algorithm, a stacked autoencoder (SAE) can relieve the pressure of labelling data…”
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Toward Robust Fault Identification of Complex Industrial Processes Using Stacked Sparse-Denoising Autoencoder With Softmax Classifier by Liu, Jinping, Xu, Longcheng, Xie, Yongfang, Ma, Tianyu, Wang, Jie, Tang, Zhaohui, Gui, Weihua, Yin, Huazhan, Jahanshahi, Hadi

“…This article proposes a robust end-to-end deep learning-induced fault recognition scheme by stacking multiple sparse-denoising autoencoders with a Softmax classifier, called stacked spare-denoising autoencoder (SSDAE…”
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Life prediction of lithium-ion batteries based on stacked denoising autoencoders by Xu, Fan, Yang, Fangfang, Fei, Zicheng, Huang, Zhelin, Tsui, Kwok-Leung

“… In this study, a deep learning-based stacked denoising autoencoder (SDAE) method is proposed to directly predict battery life by extracting various battery features…”
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Stacked Fisher autoencoder for SAR change detection by Liu, Ganchao, Li, Lingling, Jiao, Licheng, Dong, Yongsheng, Li, Xuelong

“… Stacked autoencoder is effective in image denoising and classification when it is used for synthetic aperture radar (SAR) change detection…”
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Fault prediction of combine harvesters based on stacked denoising autoencoders by Qiu, Zhaomei, Shi, Gaoxiang, Zhao, Bo, Jin, Xin, Zhou, Liming, Ma, Tengfei

“… In this study, a combine harvester fault prediction method based on a combination of stacked denoising autoencoders (SDAE…”
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Automatic Diagnosis of Microgrid Networks’ Power Device Faults Based on Stacked Denoising Autoencoders and Adaptive Affinity Propagation Clustering by Fan, Bo, Zhang, Xiaodi, Shu, Xin, Xu, Fan

“…This paper presents a model based on stacked denoising autoencoders (SDAEs) in deep learning and adaptive affinity propagation (adAP…”
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A deep learning framework for financial time series using stacked autoencoders and long-short term memory by Bao, Wei, Yue, Jun, Rao, Yulei

“… This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs…”
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Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels by Zhang, Xiaodi, Li, Xin, Shu, Xin, Xu, Fan

“… In this paper, we use the stacked denoising autoencoder (SDAE) model in deep learning to construct HI directly from the microgrid power equipment of raw signals in bearings…”
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An imbalanced data classification algorithm of improved autoencoder neural network by Chenggang Zhang, Wei Gao, Jiazhi Song, Jinqing Jiang

“… Experiment shows that, compared with the traditional stacked autoencoder neural network (SAE) and oversampling autoencoder neural network without denoising process…”
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