Search Results - Convolutional autoencoder network

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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CNNDLP: A Method Based on Convolutional Autoencoder and Convolutional Neural Network with Adjacent Edge Attention for Predicting lncRNA–Disease Associations by Xuan, Ping, Sheng, Nan, Zhang, Tiangang, Liu, Yong, Guo, Yahong

“…-source data and to learn the low-dimensional feature representations from these data. We propose a method based on the convolutional neural network with the attention…”
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Advancements in Gas Turbine Fault Detection: A Machine Learning Approach Based on the Temporal Convolutional Network–Autoencoder Model by Fahmi, Al-Tekreeti Watban Khalid, Reza Kashyzadeh, Kazem, Ghorbani, Siamak

“… For this purpose, an advanced Temporal Convolutional Network (TCN)–Autoencoder model was presented to detect anomalies in vibration data…”
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Plant disease detection using hybrid model based on convolutional autoencoder and convolutional neural network by Bedi, Punam, Gole, Pushkar

“… This paper proposes a novel hybrid model based on Convolutional Autoencoder (CAE) network and Convolutional Neural Network (CNN…”
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Predicting transonic flowfields in non–homogeneous unstructured grids using autoencoder graph convolutional networks by Immordino, Gabriele, Vaiuso, Andrea, Da Ronch, Andrea, Righi, Marcello

“… Our approach leverages geometric deep learning, specifically through the use of an autoencoder architecture built on graph convolutional networks…”
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An Elliptic Kernel Unsupervised Autoencoder-Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing by Alfaro-Mejia, Estefania, Delgado, Carlos J., Manian, Vidya

“… In the initial stage, endmember extraction and abundance map estimation are carried out using a convolutional autoencoder…”
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Segmentation of digital rock images using deep convolutional autoencoder networks by Karimpouli, Sadegh, Tahmasebi, Pejman

“…). Among them, convolutional autoencoder networks have produced accurate results in different applications when various images are available for the training…”
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Early Parkinson's Disease Prediction Using rS-fMRI Functional Connectivity and Autoencoder Graph Convolutional Network by Limas, Lesbia Lopez, Manian, Vidya

“… We propose a deep learning framework that combines resting-state functional MRI (rs-fMRI) data and a Graph Convolutional Network (GCN…”
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Multi-stage convolutional autoencoder network for hyperspectral unmixing by Yu, Yang, Ma, Yong, Mei, Xiaoguang, Fan, Fan, Huang, Jun, Li, Hao

“… Among the various linear unmixing methods, the autoencoder unmixing network has achieved superior performance and presented more significant potential because of the powerful data fitting ability…”
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Multi-level convolutional autoencoder networks for parametric prediction of spatio-temporal dynamics by Xu, Jiayang, Duraisamy, Karthik

“… A convolutional autoencoder is used as the top level to encode the high dimensional input data along spatial dimensions into a sequence of latent variables…”
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CAE-CNN: Predicting transcription factor binding site with convolutional autoencoder and convolutional neural network by Zhang, Yongqing, Qiao, Shaojie, Zeng, Yuanqi, Gao, Dongrui, Han, Nan, Zhou, Jiliu

“…•Integrate the unsupervised and supervised method to predict the TF binding site.•CAE-CNN share the parameters, so the training time can be significantly…”
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Anomaly Detection Based on Graph Convolutional Network–Variational Autoencoder Model Using Time-Series Vibration and Current Data by Choi, Seung-Hwan, An, Dawn, Lee, Inho, Lee, Suwoong

“…This paper proposes a deep learning-based anomaly detection method using time-series vibration and current data, which were obtained from endurance tests on…”
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CAD-Skin: A Hybrid Convolutional Neural Network–Autoencoder Framework for Precise Detection and Classification of Skin Lesions and Cancer by Khan, Abdullah, Sajid, Muhammad Zaheer, Khan, Nauman Ali, Youssef, Ayman, Abbas, Qaisar

“… neural networks and autoencoders to improve the classification efficiency of skin cancer…”
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Convolutional autoencoder network lithology recognition based on scratch tests by Wang, Suling, Ren, Zhihui, Dong, Kangxing, Li, Yanchun, Li, Jinbo, Wen, Pengyun, Qu, Ruyi, Li, Tingting, Wen, Zhennan

“… By integrating convolutional neural network (CNN) and auto-encode network (AE), a novel lithology identification method based on scratch data was proposed…”
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Extract features from lithium-ion battery electrochemical impedance spectra and estimate state of health based on improved convolutional autoencoder-temporal convolutional network by Lou, Cheng, Wang, Shi, Li, Zhaoting, Wang, Kai

“… into a two-dimensional image format. We have developed an improved convolutional autoencoder (ICAE…”
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Single-pixel imaging with untrained convolutional autoencoder network by Li, Zhicai, Huang, Jian, Shi, Dongfeng, Chen, Yafeng, Yuan, Kee, Hu, Shunxing, Wang, Yingjian

“…•We propose a physical model-driven untrained deep convolutional autoencoder network for SPI and validate its performance from simulations and experiments…”
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Characterization of $S_1$ and $S_2$ Heart Sounds Using Stacked Autoencoder and Convolutional Neural Network by Mishra, Madhusudhan, Menon, Hrishikesh, Mukherjee, Anirban

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Bayesian optimization and channel-fusion-based convolutional autoencoder network for fault diagnosis of rotating machinery by Zou, L., Zhuang, K.J., Zhou, A., Hu, J.

“…•A novel convolutional network based on Bayesian optimization and channel fusion mechanism is developed…”
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Within-project and cross-project just-in-time defect prediction based on denoising autoencoder and convolutional neural network by Zhu, Kun, Zhang, Nana, Ying, Shi, Zhu, Dandan

“… Therefore, the authors propose a novel just-in-time defect prediction model named DAECNN-JDP based on denoising autoencoder and convolutional neural network in this study, which has three main advantages…”
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Indoor Localization with an Autoencoder based Convolutional Neural Network by Arslantas, Hatice, Okdem, Selcuk

“… In this study, we propose a method and training strategy that is entirely based on a Convolutional Neural Network (CNN…”
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