Search Results - Robust convolutional autoencoder

Hybrid robust convolutional autoencoder for unsupervised anomaly detection of machine tools under noises by Yan, Shen, Shao, Haidong, Xiao, Yiming, Liu, Bin, Wan, Jiafu

“…•A new FDD loss function to suppress the noises is designed.•Construct the PCDF module to enhance the robustness of the network.•The unsupervised anomaly…”
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Clutter Suppression in GPR Imaging Using an Improved Robust Convolutional Autoencoder by Fan, Pengjie, Shen, Shaoxiang, Wang, Guangyu

“… We propose a clutter suppression algorithm based on an improved robust convolutional autoencoder (U‐RCAE…”
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Unsupervised Erratic Seismic Noise Attenuation With Robust Deep Convolutional Autoencoders by Qian, Feng, Guo, Wei, Liu, Zhangbo, Yu, Hongtao, Zhang, Gulan, Hu, Guangmin

“… Many erratic noise cancellation methods, for instance, robust reduced-rank and sparsity-promoting filtering, have been proven to achieve promising results in overcoming this challenge…”
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A Light-Weight and Robust Tensor Convolutional Autoencoder for Anomaly Detection by Li, Xiaocan, Xie, Kun, Wang, Xin, Xie, Gaogang, Li, Kenli, Cao, Jiannong, Zhang, Dafang, Wen, Jigang

“…-linear feature in the data. To address the issues, we propose a Robust Tensor Convolutional Autoencoder (RTCAE…”
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Photonic analog-to-digital converter powered by a generalized and robust convolutional recurrent autoencoder by Zou, Xiuting, Xu, Shaofu, Deng, Anyi, Qian, Na, Wang, Rui, Zou, Weiwen

“…We propose a convolutional recurrent autoencoder (CRAE) to compensate for time mismatches in a photonic analog-to-digital converter (PADC…”
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Deep Convolutional Autoencoders for Robust Flow Model Calibration Under Uncertainty in Geologic Continuity by Jiang, Anyue, Jafarpour, Behnam

“… We propose a deep learning architecture, known as variational auto‐encoder, for robust dimension…”
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Hybrid Attention-Enhanced Regularized Convolutional Autoencoder for Robust EEG Feature Extraction in Seizure Prediction by Chen, Yu-Hao, Chen, Hsiang-Yu, Chen, Yu-Chia, Chen, Hsuan-Fu, Chen, Hsiang-Han

“… Consequently, this study proposes a novel hybrid attention-enhanced regularized convolutional autoencoder (HA-RCAE…”
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DHCAE: Deep Hybrid Convolutional Autoencoder Approach for Robust Supervised Hyperspectral Unmixing by Hadi, Fazal, Yang, Jingxiang, Ullah, Matee, Ahmad, Irfan, Farooque, Ghulam, Xiao, Liang

“… In this paper, we present a new method for robust supervised HSU based on a deep hybrid (3D and 2D) convolutional autoencoder…”
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A convolutional autoencoder architecture for robust network intrusion detection in embedded systems by Borgioli, Niccolò, Aromolo, Federico, Thi Xuan Phan, Linh, Buttazzo, Giorgio

“…Security threats are becoming an increasingly relevant concern in cyber–physical systems. Cyber attacks on these systems are not only common today but also…”
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Pseudo-Supervised Defect Detection Using Robust Deep Convolutional Autoencoders by Alpdemir, Mahmut Nedim

“… In this paper, we illustrate the use of Robust Deep Convolutional Autoencoders (RDCAE) for defect detection, via a pseudo-supervised training process…”
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Unsupervised Convolutional Transformer Autoencoder for Robust Health Indicator Construction and RUL Prediction in Rotating Machinery by Dahal, Amrit, Huang, Hong-Zhong, Huang, Cheng-Geng, Huang, Tudi, Khanal, Smaran, Niazi, Sajawal Gul

“… Specifically, a sequential autoencoder integrating a convolutional neural network (CNN) and vision Transformer (Vi…”
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Hybrid Graph Convolutional Network With Online Masked Autoencoder for Robust Multimodal Cancer Survival Prediction by Hou, Wentai, Lin, Chengxuan, Yu, Lequan, Qin, Jing, Yu, Rongshan, Wang, Liansheng

“… This manuscript proposes a novel hybrid graph convolutional network, entitled HGCN, which is equipped with an online masked autoencoder paradigm for robust multimodal cancer survival prediction…”
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SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival by Pan, Liangrui, Peng, Yijun, Li, Yan, Wang, Xiang, Liu, Wenjuan, Xu, Liwen, Liang, Qingchun, Peng, Shaoliang

“… This paper introduces SELECTOR, a heterogeneous graph-aware network based on convolutional mask encoders for robust multimodal prediction of cancer patient survival…”
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Hybrid data-driven feature extraction-enabled surface modeling for metal additive manufacturing by Shi, Zhangyue, Mandal, Soumya, Harimkar, Sandip, Liu, Chenang

“…Metal additive manufacturing (AM) has become popular in a large variety of applications due to its excellent capabilities of handling complex geometries and…”
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Multi-loss Function in Robust Convolutional Autoencoder for Reconstruction Low-quality Fingerprint Image by Raswa, Farchan Hakim, Halberd, Franki, Harjoko, Agus, Wahyono, Lee, Chung-Ting, Li, Yung-Hui, Wang, Jia Ching

“…Our research is fingerprint reconstruction based on a convolutional autoencoder. We combine the perceptual measurement as a multi-loss function to give satisfactory weight correction, such as the structural similarity index measure (SSIM…”
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An Accurate and Robust Approach of Device-Free Localization With Convolutional Autoencoder by Zhao, Lingjun, Huang, Huakun, Li, Xiang, Ding, Shuxue, Zhao, Haoli, Han, Zhaoyang

“… Moreover, we design a three-layer convolutional autoencoder (CAE) neural network to perform unsupervised feature extraction from raw signals followed by supervised fine-tuning for classification…”
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Robust deep image clustering using convolutional autoencoder with separable discrete Krawtchouk and Hahn orthogonal moments by Bouali, Aymane, Ouariachi, Ilham El, Zahi, Azeddine, Zenkouar, Khalid

“…; however, the majority are still incapable of learning robust noise-resistant latent features, which limits the clustering performance…”
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Convolutional Autoencoder With Sequential and Channel Attention for Robust ECG Signal Denoising With Edge Device Implementation by Wicaksana Ramadhan, Alif, Kushirayati, Syifa, Aurellia, Salsabila, Luthfi Ramadhan, Mgs M., Hannan Hunafa, Muhammad, Febrian Rachmadi, Muhammad, Jasa Mantau, Aprinaldi, Nurmaini, Siti, Mandala, Satria, Jatmiko, Wisnu

“… We proposed a convolutional autoencoder with sequential and channel attention (CAE-SCA) to address this issue…”
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Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder by Xiong, Yihui, Zuo, Renguang

“… Our approach adopted a stacked convolutional denoising autoencoder (SCDAE) to extract robust features and decreased the level of sensitivity to partially corrupted data, that is, input data that are partially missing…”
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Sequential application of denoising autoencoder and long-short recurrent convolutional network for noise-robust remaining-useful-life prediction framework of lithium-ion batteries by Hong, Seonri, Kang, Moses, Kim, Jonghoon, Baek, Jongbok

“…•The denoising autoencoder is trained is follows: Gaussian noise, missing value, and the combination of two noise types…”
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