Suchergebnisse - stacked sparse autoencoder–based deep neural network

Reliable Fault Diagnosis of Rotary Machine Bearings Using a Stacked Sparse Autoencoder-Based Deep Neural Network von Sohaib, Muhammad, Kim, Jong-Myon

“… In this study, using complex envelope spectra and stacked sparse autoencoder …”
Volltext

Combustion stability monitoring through flame imaging and stacked sparse autoencoder based deep neural network von Han, Zhezhe, Hossain, Md. Moinul, Wang, Yuwei, Li, Jian, Xu, Chuanlong

“… •A novel deep learning model is established for predicting combustion stability.•Automatic generation of combustion stability label is achieved …”
Volltext

Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network von Nguyen, Cong Dai, Prosvirin, Alexander E., Kim, Cheol Hong, Kim, Jong-Myon

“… Gearbox fault diagnosis based on the analysis of vibration signals has been a major research topic for a few decades due to the advantages of vibration …”
Volltext

Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery von Qi, Yumei, Shen, Changqing, Wang, Dong, Shi, Juanjuan, Jiang, Xingxing, Zhu, Zhongkui

“… Thus, a stacked sparse autoencoder (SAE)-based machine fault diagnosis method is proposed in this paper …”
Volltext

Industrial Internet of Things Cyber Threats Detection Through Deep Feature Learning and Stacked Sparse Autoencoder Based Classification von Vijay Anand, R., Magesh, G., Alagiri, I., Brahmam, Madala Guru, Senthil Kumar, C., Kesavan, M., Abdullah, Azween Bin

“… ABSTRACT In recent times, the industrial system has integrated with industrial Internet of Things (IoT) applications to enable the ease of production process …”
Volltext

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction von Deng, Lei, Fan, Chao, Zeng, Zhiwen

“… Results In this study, we present DeepSacon, a computational method that can effectively predict protein solvent accessibility and contact number by using a deep neural network, which is built based …”
Volltext

Stacked Denoise Autoencoder Based Feature Extraction and Classification for Hyperspectral Images von Xing, Chen, Yang, Xiaoquan, Ma, Li

“… Training a deep network for feature extraction and classification includes unsupervised pretraining and supervised fine-tuning …”
Volltext

Autoencoder-based representation learning and its application in intelligent fault diagnosis: A review von Yang, Zheng, Xu, Binbin, Luo, Wei, Chen, Fei

“… In the past decades, the vigorous development of deep learning (DL) brings new opportunities for IFD, especially the representation learning based on Autoencoder (AE …”
Volltext

An efficient method for autoencoder‐based collaborative filtering von Wang, Yi‐Lei, Tang, Wen‐Zhe, Yang, Xian‐Jun, Wu, Ying‐Jie, Chen, Fu‐Ji

“… With rapid development in deep learning, neural network‐based CF models have gained great attention in the recent years, especially autoencoder‐based CF model …”
Volltext

Deep Neural Network Hardware Implementation Based on Stacked Sparse Autoencoder von Coutinho, Maria G. F., Torquato, Matheus F., Fernandes, Marcelo A. C.

“… Therefore, the objective of this paper is to propose a neural network hardware implementation to be used in deep learning applications …”
Volltext

Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network von Aslam, Muhammad Aqeel, Xue, Cuili, Chen, Yunsheng, Zhang, Amin, Liu, Manhua, Wang, Kan, Cui, Daxiang

“… In this study, we proposed a new method for feature extraction using a stacked sparse autoencoder to extract the discriminative features from the unlabeled data of breath samples …”
Volltext

Deep neural network for semi-automatic classification of term and preterm uterine recordings von Chen, Lili, Xu, Huoyao

“… For this purpose, sparse autoencoder (SAE) based deep neural network (SAE-based …”
Volltext

Optimizing MobileNetV2 for improved accuracy in early gastric cancer detection based on dynamic pelican optimizer von Zhou, Guoping, He, Qiyu, Liu, Xiaoli, Kai, Xinghua, Cao, Weikang, Ding, Junning, Zhuang, Bufeng, Xu, Shuhua, Thwin, Myo

“… The proposed approach utilizes a customized deep learning model called MobileNetV2, which is optimized using a Dynamic variant of the Pelican Optimization Algorithm (DPOA …”
Volltext

SSAE‐MLP: Stacked sparse autoencoders‐based multi‐layer perceptron for main bearing temperature prediction of large‐scale wind turbines von 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 …”
Volltext

A stacked sparse autoencoder based architecture for Punjabi and English spoken language classification using MFCC features von Arora, Vaibhav, Sood, Pulkit, Keshari, Kumar Utkarsh

“… A number of shallow architectures namely Soft-max classifier, SVM and deep architectures namely Artificial Neural Networks, SVM with Sparse Auto encoder and Softmax with sparse auto encoder …”
Volltext

Rock mass type prediction for tunnel boring machine using a novel semi-supervised method von Yu, Honggan, Tao, Jianfeng, Qin, Chengjin, Xiao, Dengyu, Sun, Hao, Liu, Chengliang

“… •A novel semi-supervised framework is proposed to predict geological type ahead of tunnel face.•The semi-supervised framework consists of a feature extractor …”
Volltext

Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning von Sun, Jiedi, Yan, Changhong, Wen, Jiangtao

“… Inspired by the idea of compressed sensing and deep learning, a novel intelligent diagnosis method is proposed for fault identification of rotating machines …”
Volltext

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia von Kim, Junghoe, Calhoun, Vince D., Shim, Eunsoo, Lee, Jong-Hwan

“… ). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech …”
Volltext

Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features von Ahmed, H.O.A., Wong, M.L.D., Nandi, A.K.

“… •Uses compressive sensing and sparse over-complete feature learning.•Uses the unsupervised sparse autoencoder for learning feature representations …”
Volltext

The Deep Neural Network Based Classification of Fingers Pattern Using Electromyography von Ahmad, Jawad, Butt, Ammar Mohsin, Hussain, Mohsin, Akbar, Muhammad Azeem, Rehman, Waheed Ur

“… ) is used to extract a total of 500 feature vectors from five fingers that are used to train an autoencoder based five-layered Deep Neural Network (DNN …”
Volltext