Search Results - deep autoencoder network

Orthogonal Nonnegative Matrix Factorization using a novel deep Autoencoder Network by Yang, Mingming, Xu, Songhua

“…) based and deep-layered structure (DLS) based models. However, SLS models cannot capture complex relationships and hierarchical information latent in a matrix due…”
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Deep Autoencoder Neural Networks: A Comprehensive Review and New Perspectives: Deep Autoencoder Neural Networks by Mienye, Ibomoiye Domor, Swart, Theo G.

“…Autoencoders have become a fundamental technique in deep learning (DL), significantly enhancing representation learning across various domains, including image processing, anomaly detection, and generative modelling…”
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Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial–temporal features extraction by D’Angelo, Gianni, Palmieri, Francesco

“… For this purpose, a novel autoencoder-based deep neural network architecture…”
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Pilots' Fatigue Status Recognition Using Deep Contractive Autoencoder Network by Wu, Edmond Q., Peng, X. Y., Zhang, Caizhi Z., Lin, J. X., Sheng, Richard S. F.

“…The evaluation of pilots' fatigue status is of substantial significance in aviation safety, which faces two major issues. They are how to get the fatigue…”
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A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network by Wang, Lei, You, Zhu-Hong, Chen, Xing, Xia, Shi-Xiong, Liu, Feng, Yan, Xin, Zhou, Yong, Song, Ke-Jian

“… In this article, we propose a new computational method for predicting DTIs from drug molecular structure and protein sequence by using the stacked autoencoder of deep learning, which can adequately…”
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DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing by Su, Yuanchao, Li, Jun, Plaza, Antonio, Marinoni, Andrea, Gamba, Paolo, Chakravortty, Somdatta

“… In this paper, we develop a new technique for unsupervised unmixing which is based on a deep autoencoder network (DAEN…”
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Predicting protein-protein interactions from protein sequences by a stacked sparse autoencoder deep neural network by Wang, Yan-Bin, You, Zhu-Hong, Li, Xiao, Jiang, Tong-Hai, Chen, Xing, Zhou, Xi, Wang, Lei

“…). Then, these extracted features were reconstructed using the stacked autoencoder. Finally, a novel…”
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Workplace Flexibility Analysis in Cyberphysical Human Systems Using Cloud-Enabled Deep Autoencoder Networks by Farashaei, Danial, Honarbakhsh, Amin, Movahedifar, Seyed Mojtaba, Shakeri, Eghbal

“…), we employed a stacked autoencoder (SAE) approach and a cloud-based computing environment. The study’s statistical population includes construction companies in Mashhad, Iran…”
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A multi–modal unsupervised fault detection system based on power signals and thermal imaging via deep AutoEncoder neural network by Cordoni, Francesco, Bacchiega, Gianluca, Bondani, Giulio, Radu, Robert, Muradore, Riccardo

“… The considered dataset is highly unbalanced with the vast majority of samples being healthy. Thermal images are processed via a Deep Convolutional neural network…”
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Recognition of geochemical anomalies using a deep autoencoder network by Xiong, Yihui, Zuo, Renguang

“… The southwestern Fujian district (China) is chosen as a case study area. A variety of learning rates, iterations, and the size of each hidden layer are constructing and training the deep autoencoder networks on all the geochemical samples…”
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Brain MRI Image Classification for Cancer Detection Using Deep Wavelet Autoencoder-Based Deep Neural Network by Kumar Mallick, Pradeep, Ryu, Seuc Ho, Satapathy, Sandeep Kumar, Mishra, Shruti, Nguyen, Gia Nhu, Tiwari, Prayag

“… Deep neural networks (DNN), till date, have demonstrated wonderful performance in classification and segmentation task…”
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Mapping soil organic carbon distribution across South Africa's major biomes using remote sensing-topo-climatic covariates and Concrete Autoencoder-Deep neural networks by Odebiri, Omosalewa, Mutanga, Onisimo, Odindi, John, Naicker, Rowan

“… In this regard, this study mapped SOC distribution across South Africa's major biomes using remotely sensed-topo-climatic data and Concrete Autoencoder-Deep neural networks (CAE-DNN…”
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Bearing remaining useful life prediction based on deep autoencoder and deep neural networks by Ren, Lei, Sun, Yaqiang, Cui, Jin, Zhang, Lin

“… optimal feature selection and efficient feature compression. This paper proposes a new deep learning based prediction framework for bearing RUL by using deep autoencoder and deep neural networks (DNN…”
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Ensemble of feature augmented convolutional neural network and deep autoencoder for efficient detection of network attacks by B, Selvakumar, M, Sivaanandh, K, Muneeswaran, B, Lakshmanan

“…). The proposed work consists of three phases: (i) Feature Augmented Convolutional Neural Network (FA-CNN) (ii) Deep Autoencoder (iii…”
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Nonlinear Unmixing of Hyperspectral Data via Deep Autoencoder Networks by Wang, Mou, Zhao, Min, Chen, Jie, Rahardja, Susanto

“… In this letter, we develop a novel blind hyperspectral unmixing scheme based on a deep autoencoder network…”
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DCDA: CircRNA–Disease Association Prediction with Feed-Forward Neural Network and Deep Autoencoder by Turgut, Hacer, Turanli, Beste, Boz, Betül

“…Circular RNA is a single-stranded RNA with a closed-loop structure. In recent years, academic research has revealed that circular RNAs play critical roles in…”
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Enhanced autoencoder and deep neural network (AE&DNN) method for ddos attack recognition by Pajila, P. J. Beslin, Robinson, Y. Harold, Allimuthu, Udayakumar, Julie, E. Golden, Jaffrin, Lijetha. C., Sheena, B. Gracelin

“… This paper proposed a security mechanism to identify DDoS attacks using enhanced AutoEncoder and Deep Neural Network (AE & DNN…”
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Data‐driven polyline simplification using a stacked autoencoder‐based deep neural network by Yu, Wenhao, Chen, Yujie

“… Then, a stacked autoencoder‐based deep neural network model is trained to learn the pattern features of polyline…”
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IoT network security using autoencoder deep neural network and channel access algorithm by Ali, Saif Mohammed, Elameer, Amer S., Jaber, Mustafa Musa

“… These attacks create security and privacy issues while making data communication. Therefore, a new method autoencoder deep neural network (AENN…”
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Infomax-based deep autoencoder network for recognition of multi-element geochemical anomalies linked to mineralization by Esmaeiloghli, Saeid, Tabatabaei, Seyed Hassan, Carranza, Emmanuel John M.

“…In recent years, deep autoencoder networks (DANs) have shown enormous potential to achieve state-of-the-art performance for recognizing multi-element geochemical anomalies related to mineralization…”
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