Suchergebnisse - sparse convolutional autoencoder (((sace OR sae) OR space))

EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder von 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 von 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 von 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 von 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 von 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 von 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 von 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 von 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 von 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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Online Public Opinion Situation Assessment by Deep Sparse Autoencoder and Time-Series Modeling Convolutional Neural Network von 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 von 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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Deep learning for pixel-level image fusion: Recent advances and future prospects von 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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Microscopic segmentation and classification of COVID‐19 infection with ensemble convolutional neural network von 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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Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models von 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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Prior knowledge embedding convolutional autoencoder: A single-source domain generalized fault diagnosis framework under small samples von 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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Temperature scaling unmixing framework based on convolutional autoencoder von 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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Early Parkinson's Disease Prediction Using rS-fMRI Functional Connectivity and Autoencoder Graph Convolutional Network von 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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Structural Damage Identification Using Autoencoders: A Comparative Study von Spínola Neto, Marcos, Finotti, Rafaelle, Barbosa, Flávio, Cury, Alexandre

“… Autoencoders, as unsupervised learning models, offer promise for SHM by learning data features and reducing dimensionality …”
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Deep Learning Augmented Data Assimilation: Reconstructing Missing Information with Convolutional Autoencoders von Wang, Yueya, Shi, Xiaoming, Lei, Lili, Fung, Jimmy Chi-Hung

“… By training a convolutional autoencoder (CAE) with a long simulation at a coarse “forecast” resolution (T63), we obtained a deep learning approximation …”
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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 von 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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