Suchergebnisse - stacked convolutional autoencoder network

Characterization of $S_1$ and $S_2$ Heart Sounds Using Stacked Autoencoder and Convolutional Neural Network von Mishra, Madhusudhan, Menon, Hrishikesh, Mukherjee, Anirban

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Two-stage multi-dimensional convolutional stacked autoencoder network model for hyperspectral images classification von Bai, Yang, Sun, Xiyan, Ji, Yuanfa, Fu, Wentao, Zhang, Jinli

“… Focused on above-mentioned problem, a novel Two-stage Multi-dimensional Convolutional Stacked Autoencoder (TMC-SAE …”
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C-SAN: Convolutional stacked autoencoder network for brain tumor detection using MRI von Gayathiri, R., Santhanam, Suganthi

“… •Pre-processing is done by Non-Local Means (NLM) filter.•Image segmentation is done using V-Net.•Brain tumour is achieved by proposed C-SAN. Magnetic Resonance …”
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A stacked autoencoder‐based convolutional and recurrent deep neural network for detecting cyberattacks in interconnected power control systems von D'Angelo, Gianni, Palmieri, Francesco

“… It is based on stacked deep neural networks, which have proven to be capable to timely identify and classify attacks, by autonomously eliciting knowledge …”
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Classification of lemon quality using hybrid model based on Stacked AutoEncoder and convolutional neural network von Yılmaz, Esra Kavalcı, Adem, Kemal, Kılıçarslan, Serhat, Aydın, Hatice Aktaş

“… Agricultural product quality assessment is crucial for determining marketability and managing waste. It helps ensure that products meet industry standards and …”
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Gait Recognition Method of Underground Coal Mine Personnel Based on Densely Connected Convolution Network and Stacked Convolutional Autoencoder von Liu, Xiaoyang, Liu, Jinqiang

“… (DenseNet) and stacked convolutional autoencoder (SCAE). The mainstream network based on DenseNet is mainly used to learn the similarity of dynamic deep features containing spatiotemporal information in the gait pattern …”
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Fault detection and recognition of multivariate process based on feature learning of one-dimensional convolutional neural network and stacked denoised autoencoder von Zhang, Chengyi, Yu, Jianbo, Wang, Shijin

“… In this paper, we propose a hybrid deep learning model (i.e. 1-DCNN + SDAE) that integrates one-dimensional convolutional neural network (1-DCNN …”
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Video surveillance image enhancement via a convolutional neural network and stacked denoising autoencoder von Che Aminudin, Muhamad Faris, Suandi, Shahrel Azmin

“… To address these issues, a deep learning image enhancement (DLIE) model is proposed. By utilizing a deep learning architecture such as a convolutional neural network (CNN …”
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An Improved Data Compression Framework for Wireless Sensor Networks Using Stacked Convolutional Autoencoder (S-CAE) von Kumble, Lithin, Patil, Kiran Kumari

“… We introduce a stacked convolutional RBM auto-encoder (stacked CAE) model for compressing sensor data, which is made up of layers …”
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Characterization of S1 and S2 Heart Sounds Using Stacked Autoencoder and Convolutional Neural Network von Mishra, Madhusudhan, Menon, Hrishikesh, Mukherjee, Anirban

“… This paper proposes a new technique for the identification of fundamental heart sounds (HSs), namely, <inline-formula> <tex-math notation="LaTeX">S_{1} …”
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Intelligent fault diagnosis method of rolling bearing based on stacked denoising autoencoder and convolutional neural network von Che, Changchang, Wang, Huawei, Ni, Xiaomei, Fu, Qiang

“… To solve those problems, an intelligent fault diagnosis model based on stacked denoising autoencoder (SDAE …”
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Characterization of [Formula Omitted] and [Formula Omitted] Heart Sounds Using Stacked Autoencoder and Convolutional Neural Network von Mishra, Madhusudhan, Menon, Hrishikesh, Mukherjee, Anirban

“… This paper proposes a new technique for the identification of fundamental heart sounds (HSs), namely, [Formula Omitted] and [Formula Omitted] from the cardiac …”
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Structural inversion of radar emitter based on stacked convolutional autoencoder and deep neural network von Jiang, Yilin, Song, Yu, Zhang, Wei, Guo, Limin

“… For this reason, a radar emitter structural inversion method is proposed based on a stacked convolutional autoencoder and deep neural network (SCAE‐DNN …”
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FA-SconvAE-LSTM: Feature-Aligned Stacked Convolutional Autoencoder with Long Short-Term Memory Network for Soft Sensor Modeling von Wu, Ping, Miao, Zengdi, Wang, Ke, Gao, Jinfeng, Zhang, Xujie, Lou, Siwei, Yang, Chunjie

“… In this study, a spatio-temporal model, termed the feature-aligned stacked convolutional autoencoder with long short-term memory, is proposed to develop soft sensors for nonlinear dynamic industrial processes …”
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An effective stacked autoencoder based depth separable convolutional neural network model for face mask detection von Balasubaramanian, Sundaravadivazhagan, Cyriac, Robin, Roshan, Sahana, Maruthamuthu Paramasivam, Kulandaivel, Chellanthara Jose, Boby

“… The COVID-19 pandemic has been infecting the entire world over the past years. To prevent the spread of COVID-19, people have acclimatised to the new normal, …”
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Stressed Vegetation Identification Under Natural Gas Microleakage From Hyperspectral Images Using Stacked Autoencoder and Multiscale Three-Dimensional Convolutional Neural Network von Xiong, Kangni, Jiang, Jinbao, Ran, Weiwei, Li, Kangning, Pan, Yingyang, Wang, Xinda

“… Leveraging the abundant spectral and spatial information in hyperspectral imagery, a novel approach combining stacked autoencoder (SAE …”
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A New SCAE-MT Classification Model for Hyperspectral Remote Sensing Images von Chen, Huayue, Chen, Ye, Wang, Qiuyue, Chen, Tao, Zhao, Huimin

“… Therefore, the stacked convolutional autoencoder network and transfer learning strategy are employed in order to design a new stacked convolutional autoencoder network model transfer (SCAE-MT …”
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Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath von Soleymani, Farzan, Paquet, Eric

“… •Extracting high-level features using restricted stacked autoencoder.•A convolutional neural network is employed to enforce the policy …”
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Visual Loop Closure Detection Based on Stacked Convolutional and Autoencoder Neural Networks von Wang, Fei, Ruan, Xiaogang, Huang, Jing

“… In this paper, a method called stacked convolutional and autoencoder neural networks is proposed to automatically extract image features and perform dimensionality reduction processing …”
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Design and implementation of an Automatic Deep Stacked Sparsely Connected Convolutional Autoencoder (ADSSCCA) neural network for remote sensing lithological mapping using calculated dropout von Atangana Otele, Charlie Gael, Akong Onabid, Mathias, Assembe, Patrick Stephane

“… In this paper, we propose the design and implementation of an Automatic Deep Stacked Sparsely Connected Convolutional Autoencoder (ADSSCCA …”
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