Search Results - "Stacked Autoencoder"

Deep learning for pixel-level image fusion: Recent advances and future prospects by Liu, Yu, Chen, Xun, Wang, Zengfu, Wang, Z. Jane, Ward, Rabab K., Wang, Xuesong

“…•The difficulties that exist in conventional image fusion research are analyzed.•The advantages of deep learning (DL) techniques for image fusion are…”
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Cascade stacked autoencoder neural network for intrusion detection in CAN-FD vehicular network by Devi, V. Anjana, Reddy, P.V. Bhaskar, Ponnada, Sreenu, Kumar, K. Suresh

“…In this work, an Intrusion Detection System (IDS) for Controller Area Network with Flexible Data Rate (CAN-FD) Vehicle Networks based on hybrid Deep Learning…”
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Transfer learning based on improved stacked autoencoder for bearing fault diagnosis by Luo, Shuyang, Huang, Xufeng, Wang, Yanzhi, Luo, Rongmin, Zhou, Qi

“…Deep transfer learning algorithm is regarded as a promising method to address the issue of rolling bearing fault diagnosis with limited labeled data. Stacked…”
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ReLTanh: An activation function with vanishing gradient resistance for SAE-based DNNs and its application to rotating machinery fault diagnosis by Wang, Xin, Qin, Yi, Wang, Yi, Xiang, Sheng, Chen, Haizhou

“…Tanh is a sigmoidal activation function that suffers from vanishing gradient problem, so researchers have proposed some alternative functions including…”
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A novel semi-supervised pre-training strategy for deep networks and its application for quality variable prediction in industrial processes by Yuan, Xiaofeng, Ou, Chen, Wang, Yalin, Yang, Chunhua, Gui, Weihua

“…•A semi-supervised autoencoder (SS-AE) is first developed as the basic network to extract quality-related features.•By hierarchically stacking multiple SS-AEs,…”
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A deep model for short-term load forecasting applying a stacked autoencoder based on LSTM supported by a multi-stage attention mechanism by Fazlipour, Zahra, Mashhour, Elaheh, Joorabian, Mahmood

“…•A new deep-stacked autoencoder model is proposed for short-term load forecasting.•A stack of autoencoders is developed to extract more latent relevant…”
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Deep Spatio-Temporal Representation for Detection of Road Accidents Using Stacked Autoencoder by Singh, Dinesh, Mohan, Chalavadi Krishna

“…Vision-based detection of road accidents using traffic surveillance video is a highly desirable but challenging task. In this paper, we propose a novel…”
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Modified Stacked Autoencoder Using Adaptive Morlet Wavelet for Intelligent Fault Diagnosis of Rotating Machinery by Shao, Haidong, Xia, Min, Wan, Jiafu, de Silva, Clarence W.

“…Intelligent fault diagnosis techniques play an important role in improving the abilities of automated monitoring, inference, and decision making for the repair…”
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Deep quality-related feature extraction for soft sensing modeling: A deep learning approach with hybrid VW-SAE by Yuan, Xiaofeng, Ou, Chen, Wang, Yalin, Yang, Chunhua, Gui, Weihua

“…Soft sensors have been extensively used to predict difficult-to-measure quality variables for effective modeling, control and optimization of industrial…”
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An innovative coupled model in view of wavelet transform for predicting short-term PM10 concentration by Qiao, Weibiao, Wang, Yining, Zhang, Jianzhuang, Tian, Wencai, Tian, Yu, Yang, Quan

“…Wavelet transform (WT) is an advanced preprocessing technique, which has been widely used in PM 10 prediction. However, this technique cannot provide stable…”
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Deep packet: a novel approach for encrypted traffic classification using deep learning by Lotfollahi, Mohammad, Jafari Siavoshani, Mahdi, Shirali Hossein Zade, Ramin, Saberian, Mohammdsadegh

“…Network traffic classification has become more important with the rapid growth of Internet and online applications. Numerous studies have been done on this…”
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Novel segmented stacked autoencoder for effective dimensionality reduction and feature extraction in hyperspectral imaging by Zabalza, Jaime, Ren, Jinchang, Zheng, Jiangbin, Zhao, Huimin, Qing, Chunmei, Yang, Zhijing, Du, Peijun, Marshall, Stephen

“…Stacked autoencoders (SAEs), as part of the deep learning (DL) framework, have been recently proposed for feature extraction in hyperspectral remote sensing…”
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Learning Compact and Discriminative Stacked Autoencoder for Hyperspectral Image Classification by Zhou, Peicheng, Han, Junwei, Cheng, Gong, Zhang, Baochang

“…As one of the fundamental research topics in remote sensing image analysis, hyperspectral image (HSI) classification has been extensively studied so far…”
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Diagnosis of breast cancer with Stacked autoencoder and Subspace kNN by Adem, Kemal

“…Breast cancer is one of the most common and deadliest cancer types in women worldwide. Research on this disease has become very important because early…”
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Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE by Yuan, Xiaofeng, Huang, Biao, Wang, Yalin, Yang, Chunhua, Gui, Weihua

“…In modern industrial processes, soft sensors have played an important role for effective process control, optimization, and monitoring. Feature representation…”
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Remaining useful life prediction of bearing based on stacked autoencoder and recurrent neural network by Han, Tian, Pang, Jiachen, Tan, Andy C.C.

“…•A new life prediction of faulty rolling bearing method based on Stacked Autoencoder and Recurrent Neural Network.•To minimize human interference in the…”
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Abnormal Driving Detection With Normalized Driving Behavior Data: A Deep Learning Approach by Hu, Jie, Zhang, Xiaoqin, Maybank, Stephen

“…Abnormal driving may cause serious danger to both the driver and the public. Existing detectors of abnormal driving behavior are mainly based on shallow…”
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Stacked autoencoder-based community detection method via an ensemble clustering framework by Xu, Rongbin, Che, Yan, Wang, Xinmei, Hu, Jianxiong, Xie, Ying

“…Community detection is a challenging issue because most existing methods are not well suited for complex social networks with ambiguous structures. In this…”
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Layer-wise Residual-guided Feature Learning with Deep Learning Networks for Industrial Quality Prediction by Wang, Yalin, Luo, Jiang, Liu, Chenliang, Yuan, Xiaofeng, Wang, Kai, Yang, Chunhua

“…Deep learning has been widely used in quality prediction of industrial process data due to its powerful feature extraction capability. However, the limitation…”
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Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath by Soleymani, Farzan, Paquet, Eric

“…•Deep reinforcement learning framework called DeepBreath for portfolio management.•Extracting high-level features using restricted stacked autoencoder.•A…”
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