Search Results - deep stacked denoising autoencoder

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…”
Get full text

A selective deep stacked denoising autoencoders ensemble with negative correlation learning for gearbox fault diagnosis by Yu, Jianbo

“… This paper proposes a selective stacked denoising autoencoders (SDAE) with negative correlation learning (NCL) (SSDAE-NCL…”
Get full text

Monitoring of complex profiles based on deep stacked denoising autoencoders by Chen, Shumei, Yu, Jianbo, Wang, Shijin

“…Fig. 4. Schematic diagram of the SDAE-based model for profile monitoring. [Display omitted] •DNN is developed for modelling complex profiles.•SDAE is effective…”
Get full text

Deep feature fusion‐based stacked denoising autoencoder for tag recommendation systems by Fei, Zhengshun, Wang, Jinglong, Liu, Kangling, Attahi, Eric, Huang, Bingqiang

“…With the rapid development of artificial intelligence technology, commercial robots have gradually entered our daily lives. In order to promote product…”
Get full text

Face recognition via Deep Stacked Denoising Sparse Autoencoders (DSDSA) by Görgel, Pelin, Simsek, Ahmet

“… In this paper, the proposed face recognition system namely Deep Stacked Denoising Sparse Autoencoders (DSDSA…”
Get full text

Automated atrial fibrillation classification based on denoising stacked autoencoder and optimized deep network by Singh, Prateek, Sharma, Ambalika, Maiya, Shreesha

“… With this in mind, the two-fold study is proposed, in which three denoising autoencoders for ECG signal pre-processing were evaluated and compared…”
Get full text

Deep Learning-Based Stacked Denoising and Autoencoder for ECG Heartbeat Classification by Nurmaini, Siti, Darmawahyuni, Annisa, Sakti Mukti, Akhmad Noviar, Rachmatullah, Muhammad Naufal, Firdaus, Firdaus, Tutuko, Bambang

“… To overcome such drawbacks, deep learning (DL) is proposed in the pre-training and fine-tuning phases to produce an automated feature representation for multi-class classification…”
Get full text

Multi-source deep transfer learning with stacked denoising autoencoder and Wasserstein distance for wind power prediction in new wind farm by Xu, Haiyan, Hao, Wenguang, Zhao, Yong, Tian, Hongda

“…•Stacked denoising autoencoder is used to establish feature correlations between the source and target domain…”
Get full text

The pre-trained explainable deep learning model with stacked denoising autoencoders for slope stability analysis by Lin, Shan, Dong, Miao, Cao, Xitailang, Liang, Zenglong, Guo, Hongwei, Zheng, Hong

“… In this work, we proposed a deeply-integrated explainable pre-trained deep learning framework with stacked denoising autoencoders in the assessment of slope stability…”
Get full text

Temporal denoising and deep feature learning for enhanced defect detection in thermography using stacked denoising convolution autoencoder by Yerneni, Naga Prasanthi, Ghali, V.S., Vesala, G.T., Wang, Fei, Mulaveesala, Ravibabu

“…•Temporal denoising of thermal profiles along with deep feature learning for enhanced defect detection in FMTWI is highlighted through a stacked denoising convolution autoencoder…”
Get full text

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…”
Get full text

An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition by Wang, Zirui, Wang, Jun, Wang, Youren

“…•A new diagnostic model named SDAE-GAN is proposed.•The model combines Generative Adversarial Networks and Stacked Denoising Autoencoders…”
Get full text

Deep learning framework designed for high-performance lithium-ion batteries state monitoring by Takyi-Aninakwa, Paul, Wang, Shunli, Liu, Guangchen, Fernandez, Carlos, Kang, Wenbin, Song, Yingze

“… In this work, a deep-stacked denoising autoencoder is established for a long short-term memory model that incorporates a transfer learning mechanism to estimate and study the SOC from an electrochemical perspective…”
Get full text

Demodulating Optical Wireless Communication of FBG Sensing with Turbulence-Caused Noise by Stacked Denoising Autoencoders and the Deep Belief Network by Bogale, Shegaw Demessie, Yao, Cheng-Kai, Manie, Yibeltal Chanie, Dehnaw, Amare Mulatie, Tefera, Minyechil Alehegn, Li, Wei-Long, Zhong, Zi-Gui, Peng, Peng-Chun

“… This work aims to deep denoise sensed signals from fiber Bragg grating (FBG) sensors based on FSO link transmission using advanced denoising deep learning techniques, such as stacked denoising autoencoders (SDAE…”
Get full text

Stepwise Inertial Intelligent Control of Wind Power for Frequency Regulation Based on Stacked Denoising Autoencoder and Deep Neural Network by WANG Yalun, ZHOU Tao, CHEN Zhong, WANG Yi, QUAN Hao

“… In order to realize the optimal stepwise inertial fast control of wind power frequency regulation in load disturbance events, this paper introduces the deep learning algorithm and proposes a stepwise…”
Get full text

Deep learning for electrolysis process anode effect prediction based on long short-term memory network and stacked denoising autoencoder by Yin, Gang, Li, Yi-Hui, Yan, Fei-Ya, Quan, Peng-Cheng, Wang, Min, Cao, Wen-Qi, Xu, Heng-Quan, Lu, Jian, He, Wen

“… A stacked denoising autoencoder is utilized to denoise and extract features from a large number of long-period parameter data…”
Get full text

Software defect prediction using stacked denoising autoencoders and two-stage ensemble learning by Tong, Haonan, Liu, Bin, Wang, Shihai

“… Although stacked denoising autoencoders (SDAEs) are powerful for feature learning and have been successfully applied in other fields, to the best of our knowledge, it has not been investigated in the field of SDP…”
Get full text

Identification of Uyghur Event Coreference Relationship Based on Stacked Denoising Autoencoder by WANG Shuyuana,TIAN Shengwei,YU Long,FENG Guanjun,AISHAN Wumaier,LI Pu,ZHAO Jianguo

“…Based on the characteristics of Uyghur language,a method of identifying Uyghur language event coreference relationship based on Stacked Denoising Autoencoder(SDAE…”
Get full text

A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging by Zhou, Xin, Zhao, Chunjiang, Sun, Jun, Cao, Yan, Yao, Kunshan, Xu, Min

“…) and stacked denoising autoencoder (SDAE) for extracting deep features of heavy metal lead (Pb) detection of oilseed rape leaves…”
Get full text

Fully convolutional Deep Stacked Denoising Sparse Auto encoder network for partial face reconstruction by Dinesh, P.S., Manikandan, M.

“…•In this partial face detection (PFD) is used to overcome the challenges involved in face detection and reconstruction.•A novel PFD algorithm called Self-…”
Get full text