Výsledky vyhledávání - "residual convolutional autoencoder"

One-Dimensional Residual Convolutional Autoencoder Based Feature Learning for Gearbox Fault Diagnosis Autor Yu, Jianbo, Zhou, Xingkang

“… In this article, a new DNN, one-dimensional residual convolutional autoencoder (1-DRCAE), is proposed for learning features from vibration signals directly in an unsupervised-learning way…”
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Pulsar candidate selection with residual convolutional autoencoder Autor Yin, Qian, Li, Jiajie, Zheng, Xin, Li, Yefan, Cui, Hanshuai, Bao, Zelun

“… In this paper, we design a residual convolutional autoencoder (RCAE) based on the structure of the autoencoder, and combine with logistic regression (LR…”
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Semi-supervised underwater acoustic source localization based on residual convolutional autoencoder Autor Jin, Pian, Wang, Biao, Li, Lebo, Chao, Peng, Xie, Fangtong

“…Passive localization of underwater targets was a thorny problem in underwater acoustics. For traditional model-driven passive localization methods, the main…”
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Attention model based on one-dimensional residual convolutional autoencoder and GRU for knowledge tracing Autor Ai, Lingmei, Zhang, Xiaoying

“… Therefore, an attention knowledge tracing model based on one-dimensional residual convolutional autoencoder and GRU is proposed in this paper…”
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Traffic sign classification with deformable convolution based on denoising residual convolutional autoencoder region localization Autor Pan, Hao, Guo, Qianlu, Yuan, Decheng, Pan, Duotao, Li, Dong, Yu, Qianxin

“… autoencoder for important region localization and deformable convolution (DRCAE-DCN). The denoising residual convolutional autoencoder is used to extract feature…”
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A Residual Convolutional Autoencoder-Based Structural Damage Detection Approach for Deep-Sea Mining Riser Considering Data Fusion Autor Jiang, Yufeng, Zheng, Zepeng, Liu, Yu, Wang, Shuqing, Liu, Yuchi, Yang, Zeyun, Yang, Yuan

“…A deep-sea riser is a crucial component of the mining system used to lift seafloor mineral resources to the vessel. Even minor damage to the riser can lead to…”
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BORCAE: Bayesian Optimized Residual Convolutional Autoencoder for Efficient Feedback Compression in RIS-Assisted Time-Varying IoT Networks Autor Bhardwaj, Vikash Kumar, Singh, Abhishek, Sharma, Shourya, Shukla, Mahendra K., Pandey, Om Jee

“… In this work, we propose Bayesian Optimized Residual Convolutional AutoEncoder (BORCAE), a lightweight and noise-resilient feedback compression framework based on a 1D Convolutional Autoencoder with residual connections…”
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Residual convolutional autoencoder combined with a non-negative matrix factorization to estimate fetal heart rate Autor Lafaye de Micheaux, Hugo, Resendiz, Mariel, Rivet, Bertrand, Fontecave-Jallon, Julie

“… In this context, we propose a deep residual convolutional autoencoder network trained on synthetic aECG simulations followed by a transfer learning phase on real aECG recordings to extract the cleanest fECG…”
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Radio Galaxy Morphology Generation using Residual Convolutional Autoencoder and Gaussian Mixture Models Autor Ma, Zhixian, Zhu, Jie, Li, Weitian, Xu, Haiguang

“…) using residual convolutional autoencoder (RCAE) and Gaussian mixture models (GMMs). The encoder and decoder subnets in the RCAE are symmetric aside a fully-connected…”
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RAECAE: A Multi-Scale Attention Residual Convolutional Autoencoder-Based Method for Denoising Vibration Signals of Wind Turbine Rolling Bearings Autor Zhou, Xinxin, Zhang, Jinye, Zhang, Hongrui, Yi, Hui

“… To minimize the interference of noise, this paper proposes a multiscale attention residual convolutional autoencoder-based method…”
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EMTD-SSC: An Enhanced Malicious Traffic Detection Model Using Transfer Learning Under Small Sample Conditions in IoT Autor Ge, Yueqin, Gao, Yali, Li, Xiaoyong, Cai, Binsi, Xi, Jinwen, Yu, Shui

“…In the Internet of Things (IoT) scenario, the device diversity and data sparsity present a significant challenge for malicious traffic detection, notably the…”
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SRCAE-STCBiGRU: a fused deep learning model for remaining useful life prediction of rolling bearings Autor Deng, Linfeng, Yan, Xinhui, Li, Wei

“… for the convolutional neural networks. To solve the problem, this paper proposes a RUL prediction framework based on stacked residual convolutional autoencoder and spatio-temporal convolutional bidirectional gated recurrent unit…”
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Testing Scenario Identification for Automated Vehicles Based on Deep Unsupervised Learning Autor Liu, Shuai, Ren, Fan, Li, Ping, Li, Zhijie, Lv, Hao, Liu, Yonggang

“…: typical scenarios and extreme scenarios. Secondly, a one-dimensional residual convolutional autoencoder (1D-RCAE…”
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A Load Type Identification Method of Distribution Network for Under Frequency Load Shedding Autor Dong, Jiahang, Yan, Zhenhong, Chu, Tianfeng, Zhu, Tianyi, Zhao, Zhixuan, Ma, Jiajun, Wang, Ning

“… In the process of dimensionality reduction, the residual module is introduced to strengthen the feature extraction ability, and the one dimensional residual convolutional autoencoder (1D-RCAE…”
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Compressed Sensing MRI Reconstruction Using a Generative Adversarial Network With a Cyclic Loss Autor Quan, Tran Minh, Nguyen-Duc, Thanh, Jeong, Won-Ki

“…Compressed sensing magnetic resonance imaging (CS-MRI) has provided theoretical foundations upon which the time-consuming MRI acquisition process can be…”
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Data-driven seismic prestack velocity inversion via combining residual network with convolutional autoencoder Autor Liu, Guanchao, Zhang, Lei, Wang, Qingzhen, Xu, Jianhua

“…•A residual convolutional autoencoder is proposed for 2D to 1D velocity reduction…”
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A hybrid semantic attribute-based zero-shot learning model for bearing fault diagnosis under unknown working conditions Autor Shang, Zhiwu, Tang, Lutai, Pan, Cailu, Cheng, Hongchuan

“…Most current intelligent fault diagnosis models, dependent on specific working condition data for training, cannot effectively diagnose faults in unknown…”
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Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering Autor Cai, Yaoming, Zeng, Meng, Cai, Zhihua, Liu, Xiaobo, Zhang, Zijia

“…•A novel deep subspace clustering method is proposed.•Global graph structure is modeled into the method.•A novel residual auto-encoder is designed as the…”
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Bi-READ: Bi-Residual AutoEncoder based feature enhancement for video anomaly detection Autor Kommanduri, Rangachary, Ghorai, Mrinmoy

“… To address this challenge, an end-to-end unsupervised feature enhancement network, namely Bi-Residual Convolutional AutoEncoder (Bi-ResCAE…”
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Semi-supervised learning for real-time anomaly detection in pulsed transfer wire arc additive manufacturing Autor Mattera, Giulio, Polden, Joseph, Caggiano, Alessandra, Nele, Luigi, Pan, Zengxi, Norrish, John

“…In Wire-Arc Additive Manufacturing (WAAM), ensuring the quality and integrity of components is of key importance and performing anomaly detection during…”
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