Výsledky vyhledávání - sparse convolutional autoencoder ((((same OR space) OR sae) OR sage))

EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder Autor Liu, Junxiu, Wu, Guopei, Luo, Yuling, Qiu, Senhui, Yang, Su, Li, Wei, Bi, Yifei

“…), Sparse Autoencoder (SAE), and Deep Neural Network (DNN) together. In the proposed network, the features extracted by the CNN are first sent to SAE for encoding and decoding…”
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Static video summarization using multi-CNN with sparse autoencoder and random forest classifier Autor Nair, Madhu S., Mohan, Jesna

“…). The features are extracted using four pre-trained models of CNN. These vectors are fed to Sparse Autoencoder, which outputs a combined representation of the input feature vectors…”
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SV-SAE: Layer-Wise Pruning for Autoencoder Based on Link Contributions Autor Rheey, Joohong, Park, Hyunggon

“… The resulting pruned model is referred to as a Shapley Value-based Sparse AutoEncoder (SV-SAE). Using cooperative game theory, the proposed algorithm models the autoencoder…”
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A novel multichannel sparse convolutional autoencoder for electrocardiogram signal compression Autor Bekiryazıcı, Tahir, Damkacı, Mehmet, Aydemir, Gürkan, Gürkan, Hakan

“… Deep neural networks, particularly autoencoders, offer significant potential for compressing ECG signals by mapping them to lower-dimensional spaces…”
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DOA estimation method for sparse arrays based on deep convolutional autoencoder and deep convolutional neural network Autor Guo, Shuhan, Zhang, Qin, Fu, Xiaolong, Zheng, Guimei, Zhou, Hao

“…This paper proposes a Direction-of-Arrival (DOA) estimation method based on Deep Convolutional Autoencoder (DCAE…”
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TumorAwareNet: Deep representation learning with attention based sparse convolutional denoising autoencoder for brain tumor recognition Autor Bodapati, Jyostna Devi, Balaji, Bharadwaj Bagepalli

“…) images suitable for effective tumor recognition. The proposed model employs a Sparse Convolutional Denoising Autoencoder (SCDA…”
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Transfer learning based on improved stacked autoencoder for bearing fault diagnosis Autor Luo, Shuyang, Huang, Xufeng, Wang, Yanzhi, Luo, Rongmin, Zhou, Qi

“… Stacked autoencoder (SAE) has been widely employed in deep transfer learning research since it is a semi-supervised algorithm…”
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HRPnet: High-Dimensional Feature Mapping for Radar Space Target Recognition Autor Dong, Jian, She, Qingqing, Hou, Feifei

“…), radar cross section (RCS), and polarization (POL) data obtained from the radar. First, a sparse autoencoder (SAE…”
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XAI-DSCSA: explainable-AI-based deep semi-supervised convolutional sparse autoencoder for facial expression recognition Autor Mohana, M., Subashini, P., Ghinea, George

“… as the Deep Semi-supervised Convolutional Sparse Autoencoder to address the aforementioned issues and enhance FER performance and prediction…”
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Deep learning for pixel-level image fusion: Recent advances and future prospects Autor Liu, Yu, Chen, Xun, Wang, Zengfu, Wang, Z. Jane, Ward, Rabab K., Wang, Xuesong

“… By integrating the information contained in multiple images of the same scene into one composite image, pixel-level image fusion is recognized as having high significance in a variety of fields…”
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Online Public Opinion Situation Assessment by Deep Sparse Autoencoder and Time-Series Modeling Convolutional Neural Network Autor Sun, Wei, Xiao, Ran, Li, Xuanmo

“… This model employs Deep Sparse Autoencoder (DSAE) and Time-Series Modeling Convolutional Neural Networks (TBSMA-CNN…”
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CWGAN-Based Channel Modeling of Convolutional Autoencoder-Aided SCMA for Satellite-Terrestrial Communication Autor Li, Dongbo, Liu, Xiangyu, Yin, Zhisheng, Cheng, Nan, Liu, Jie

“… In this article, a convolutional autoencoder-aided SCMA paradigm based on the stochastic channel modeling and autoencoder structure is developed…”
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Microscopic segmentation and classification of COVID‐19 infection with ensemble convolutional neural network Autor 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…”
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Feature extraction of fields of fluid dynamics data using sparse convolutional autoencoder Autor Obayashi, Wataru, Aono, Hikaru, Tatsukawa, Tomoaki, Fujii, Kozo

“… The technique here is based on the convolutional and sparse autoencoder learning algorithms and is called sparse convolutional autoencoder…”
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Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models Autor Melo, Renato, Finotti, Rafaelle, Guedes, António, Gonçalves, Vítor, Meixedo, Andreia, Ribeiro, Diogo, Barbosa, Flávio, Cury, Alexandre

“…), Sparse AutoEncoder (SAE), and Convolutional AutoEncoder (CAE)—to detect and quantify structural anomalies in railway vehicle wheels, such as polygonization…”
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Temperature scaling unmixing framework based on convolutional autoencoder Autor Xu, Jin, Xu, Mingming, Liu, Shanwei, Sheng, Hui, Yang, Zhiru

“…•The framework is a new spatial level constraint method and can be transferred to other convolutional autoencoder-based methods…”
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Prior knowledge embedding convolutional autoencoder: A single-source domain generalized fault diagnosis framework under small samples Autor Lu, Feiyu, Tong, Qingbin, Jiang, Xuedong, Du, Xin, Xu, Jianjun, Huo, Jingyi

“… generalization fault diagnosis (SDGFD) framework, the prior knowledge embedded convolutional autoencoder (PKECA), is proposed…”
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Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network Autor Yang, Pu, Wen, Chenwan, Geng, Huilin, Liu, Peng

“…This paper introduces a new intelligent fault diagnosis method based on stack pruning sparse denoising autoencoder and convolutional neural network (sPSDAE-CNN…”
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3D Segmentation of Perivascular Spaces on T1-Weighted 3 Tesla MR Images With a Convolutional Autoencoder and a U-Shaped Neural Network Autor Boutinaud, Philippe, Tsuchida, Ami, Laurent, Alexandre, Adonias, Filipa, Hanifehlou, Zahra, Nozais, Victor, Verrecchia, Violaine, Lampe, Leonie, Zhang, Junyi, Zhu, Yi-Cheng, Tzourio, Christophe, Mazoyer, Bernard, Joliot, Marc

“…We implemented a deep learning (DL) algorithm for the 3-dimensional segmentation of perivascular spaces (PVSs…”
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Early Parkinson's Disease Prediction Using rS-fMRI Functional Connectivity and Autoencoder Graph Convolutional Network Autor 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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