Search Results - stack autoencoder (SAE)

A Just-in-Time Fine-Tuning Framework for Deep Learning of SAE in Adaptive Data-Driven Modeling of Time-Varying Industrial Processes by Wu, Yijun, Liu, Diju, Yuan, Xiaofeng, Wang, Yalin

“… This may cause their performance degradation in time-varying processes. To deal with this problem, an adaptive updating framework is proposed for deep learning, which is based on just-in-time fine-tuning of stacked autoencoder (JIT-SAE…”
Get full text

Deep Adversarial Domain Adaptation Model for Bearing Fault Diagnosis by Liu, Zhao-Hua, Lu, Bi-Liang, Wei, Hua-Liang, Chen, Lei, Li, Xiao-Hua, Ratsch, Matthias

“…: the source domain and the target domain are inconsistent in their distribution. First, a deep stack autoencoder (DSAE…”
Get full text

SAE+LSTM: A New Framework for Emotion Recognition From Multi-Channel EEG by Xing, Xiaofen, Li, Zhenqi, Xu, Tianyuan, Shu, Lin, Hu, Bin, Xu, Xiangmin

“… Specially, Stack AutoEncoder (SAE) is used to build and solve the linear EEG mixing model and the emotion timing model is based on the Long Short-Term Memory Recurrent Neural Network (LSTM-RNN…”
Get full text

Damage characterization using CNN and SAE of broadband Lamb waves by Gao, Fei, Hua, Jiadong

“…) and stack autoencoder (SAE) are promising to extract features from Lamb wave signals that can be linked with damage for subsequent localization and quantification…”
Get full text

Microscopic segmentation and classification of COVID‐19 infection with ensemble convolutional neural network by Amin, Javeria, Anjum, Muhammad Almas, Sharif, Muhammad, Rehman, Amjad, Saba, Tanzila, Zahra, Rida

“… In Phase III, segmented images are passed to the stack sparse autoencoder (SSAE…”
Get full text

Fault Diagnosis of Rolling Bearings Based on an Improved Stack Autoencoder and Support Vector Machine by Cui, Mingliang, Wang, Youqing, Lin, Xinshuang, Zhong, Maiying

“… To solve this issue, this study proposes a feature distance stack autoencoder (FD-SAE) for rolling bearing fault diagnosis…”
Get full text

A Deep-Learning-Based Health Indicator Constructor Using Kullback–Leibler Divergence for Predicting the Remaining Useful Life of Concrete Structures by Nguyen, Tuan-Khai, Ahmad, Zahoor, Kim, Jong-Myon

“…This paper proposes a new technique for the construction of a concrete-beam health indicator based on the Kullback–Leibler divergence (KLD) and deep learning…”
Get full text

Deep Neural Network Based on A Stacked Autoencoder For 3D-Finger Knuckle Recognition by Al-Janabi, Dua'a Hamed, Al-Juboori, Ali Mohsin

“… This paper offers an effective deep learning technique, stacked sparse autoencoders (SSAEs), to identify the individual through a 3d finger knuckle…”
Get full text

Deep Nonlinear Dynamic Feature Extraction for Quality Prediction Based on Spatiotemporal Neighborhood Preserving SAE by Liu, Chenliang, Wang, Kai, Wang, Yalin, Xie, Shengli, Yang, Chunhua

“… Therefore, a novel spatiotemporal neighborhood preserving stack autoencoder (STNP-SAE) is proposed to simultaneously learn deep nonlinear static and dynamic features of process data in this article…”
Get full text

Multi-Gate Mixture-of-Experts Stacked Autoencoders for Quality Prediction in Blast Furnace Ironmaking by Zhu, Hongyu, He, Bocun, Zhang, Xinmin

“… However, most of the existing product quality prediction models, such as the stacked autoencoder (SAE…”
Get full text

Stacked Autoencoders Driven by Semi-Supervised Learning for Building Extraction from near Infrared Remote Sensing Imagery by Protopapadakis, Eftychios, Doulamis, Anastasios, Doulamis, Nikolaos, Maltezos, Evangelos

“…In this paper, we propose a Stack Auto-encoder (SAE)-Driven and Semi-Supervised (SSL)-Based Deep Neural Network…”
Get full text

Short-Term Streamflow Forecasting Using the Feature-Enhanced Regression Model by Bai, Yun, Bezak, Nejc, Sapač, Klaudija, Klun, Mateja, Zhang, Jin

“…), which combined stack autoencoder (SAE) with long short-term memory (LSTM). This model had two constituents…”
Get full text

Novel Manifold Autoencoder for Industrial Process Fault Diagnosis by He, Yan-Lin, Lu, Zi-Yang, Zhu, Qun-Xiong

“… In the realm of fault diagnosis, stack autoencoders (SAE) have gained widespread popularity for their robust nonlinear feature extraction…”
Get full text

Deep Feature Learning Architectures for Daily Reservoir Inflow Forecasting by Li, Chuan, Bai, Yun, Zeng, Bo

“…, deep restricted Boltzmann machine (DRBM) and stack Autoencoder (SAE), respectively, are introduced in this paper…”
Get full text

Deep learning-based protoacoustic signal denoising for proton range verification by Wang, Jing, Sohn, James J, Lei, Yang, Nie, Wei, Zhou, Jun, Avery, Stephen, Liu, Tian, Yang, Xiaofeng

“…Proton therapy is a type of radiation therapy that can provide better dose distribution compared to photon therapy by delivering most of the energy at the end…”
Get full text

Indian classical musical instrument classification using Timbral features by Gulhane, Sushen Rameshpant, Shirbahadurkar, Suresh Damodar, Badhe, Sanjay Shrikrushna

“…‐based stacked autoencoder. The significance of this research is based on the proposed Cuckoo…”
Get full text

Stack Autoencoder Transfer Learning Algorithm for Bearing Fault Diagnosis Based on Class Separation and Domain Fusion by Sun, Meidi, Wang, Hui, Liu, Ping, Huang, Shoudao, Wang, Pan, Meng, Jinhao

“… In this article, we propose a stack autoencoder transfer learning algorithm based on the class separation and domain fusion (SAE-CSDF…”
Get full text

A hybrid framework for predicting the remaining useful life of battery using Gaussian process regression by Li, Jiabo, Ye, Min, Wang, Yan, Wang, Qiao, Wei, Meng

“…) based on automatic stack autoencoder (SAE) and improved whale optimization algorithm (WOA) is proposed in this research paper…”
Get full text

Intrusion Detection Model Based on SAE and BALSTM by Jiajia, Fan, Jiangfeng, Xu, Junfeng, Zhang

“…, an intrusion detection model based on improved Stack autoencoder (SAE) and bidirectional feature attention short-time memory network (BALSTM) is proposed…”
Get full text

Rolling Bearing Fault Diagnosis Based on Stacked Autoencoder Network with Dynamic Learning Rate by Binama, Maxime, Xu, Jin-Jun, Tang, Wei, Pan, Hong

“…Fault diagnosis is of great significance for ensuring the safety and reliable operation of rolling bearing in industries. Stack autoencoder (SAE…”
Get full text