Search Results - "aautoencoder"

Transformer fault diagnosis using continuous sparse autoencoder by Wang, Lukun, Zhao, Xiaoying, Pei, Jiangnan, Tang, Gongyou

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Fusing Heterogeneous Features From Stacked Sparse Autoencoder for Histopathological Image Analysis by Zhang, Xiaofan, Dou, Hang, Ju, Tao, Xu, Jun, Zhang, Shaoting

“… from the cell detection results by a stacked sparse autoencoder. Because of the dramatically different characteristics and representations of these heterogeneous features (i.e…”
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DDSA: A Defense Against Adversarial Attacks Using Deep Denoising Sparse Autoencoder by Bakhti, Yassine, Fezza, Sid Ahmed, Hamidouche, Wassim, Deforges, Olivier

“… In this paper, we propose a novel defense solution based on a Deep Denoising Sparse Autoencoder (DDSA…”
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Attention-based Wavenet Autoencoder for Universal Voice Conversion by Polyak, Adam, Wolf, Lior

“…We present a method for converting any voice to a target voice. The method is based on a WaveNet autoencoder, with the addition of a novel attention component…”
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Phrase embedding learning from internal and external information based on autoencoder by Li, Rongsheng, Yu, Qinyong, Huang, Shaobin, Shen, Linshan, Wei, Chi, Sun, Xuewei

“…•We propose an autoencoder-based method to generate phrase embedding.•The method uses full connected network, LSTM and attention to get phrase embedding.•The…”
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Intelligent Bearing Fault Diagnosis Method Combining Compressed Data Acquisition and Deep Learning by Sun, Jiedi, Yan, Changhong, Wen, Jiangtao

“…Effective intelligent fault diagnosis has long been a research focus on the condition monitoring of rotary machinery systems. Traditionally, time-domain…”
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Hybrid Deep Learning for Botnet Attack Detection in the Internet-of-Things Networks by Popoola, Segun I., Adebisi, Bamidele, Hammoudeh, Mohammad, Gui, Guan, Gacanin, Haris

“… In this article, we reduce the feature dimensionality of large-scale IoT network traffic data using the encoding phase of long short-term memory autoencoder (LAE…”
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An ensemble learning framework for anomaly detection in building energy consumption by Araya, Daniel B., Grolinger, Katarina, ElYamany, Hany F., Capretz, Miriam A.M., Bitsuamlak, Girma

“…During building operation, a significant amount of energy is wasted due to equipment and human-related faults. To reduce waste, today's smart buildings monitor…”
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A Learning-Based Multimodel Integrated Framework for Dynamic Traffic Flow Forecasting by Zhou, Teng, Han, Guoqiang, Xu, Xuemiao, Han, Chu, Huang, Yuchang, Qin, Jing

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Data-driven flatness intelligent representation method of cold rolled strip by Xu, Yang-huan, Wang, Dong-cheng, Duan, Bo-wei, Liu, Hong-min

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Graph generative and adversarial strategy-enhanced node feature learning and self-calibrated pairwise attribute encoding for prediction of drug-related side effects by Ping Xuan, Kai Xu, Hui Cui, Toshiya Nakaguchi, Tiangang Zhang

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Deep learning enabled Lagrangian particle trajectory simulation by Gan, Jingwei, Liu, Pai, Chakrabarty, Rajan K.

“… – the variational autoencoder (VAE) and the generative adversarial net (GAN). The performance of both models was then benchmarked according to statistical analysis…”
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Leveraging latent representations for milk yield prediction and interpolation using deep learning by Liseune, Arno, Salamone, Matthieu, Van den Poel, Dirk, Van Ranst, Bonifacius, Hostens, Miel

“…•Inferring milk yields along the entire lactation curve by using deep learning.•Extracting a latent representation of a lactation curve with autoencoders…”
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Extended Pipeline for Content-Based Feature Engineering in Music Genre Recognition by Raissi, Tina, Tibo, Alessandro, Bientinesi, Paolo

“…, determined by an autoencoder. The results of the experiments conducted on GTZAN dataset reveal a noticeable contribution of this methodology towards the model's…”
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Robustifying models against adversarial attacks by Langevin dynamics by Srinivasan, Vignesh, Rohrer, Csaba, Marban, Arturo, Müller, Klaus-Robert, Samek, Wojciech, Nakajima, Shinichi

“… To achieve this task, we introduce a generative model of the conditional distribution of the inputs given labels that can be learned through a supervised Denoising Autoencoder (sDAE…”
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Deeppipe: A semi-supervised learning for operating condition recognition of multi-product pipelines by Zheng, Jianqin, Du, Jian, Liang, Yongtu, Liao, Qi, Li, Zhengbing, Zhang, Haoran, Wu, Yi

“… time series of the operating data. Then stacked autoencoder…”
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Robustifying models against adversarial attacks by Langevin dynamics by Shinichi Nakajima, Arturo Marban, Vignesh Srinivasan, Csaba Rohrer, Klaus-Robert Müller, Wojciech Samek

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GAD-VAE: generative adversarial disentanglement with variational autoencoders for hair removal in dermoscopy images by Bardou, Dalal, Lv, Laishui, Medjadba, Yasmine, Zhang, Ting, Chouhal, Ouahiba, Bounezra, Mourad, Saidi, Karima, Bezza, Youcef, Snani, Aissa

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Deeppipe: A semi-supervised learning for operating condition recognition of multi-product pipelines by Jianqin Zheng, Jian Du, Yongtu Liang, Qi Liao, Zhengbing Li, Haoran Zhang, Yi Wu

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Data-driven Non-uniform Filterbanks Based on F-ratio for Machine Anomalous Sound Detection by Li, Kai, Tran, Dung Kim, Lu, Xugang, Akagi, Masato, Unoki, Masashi

“…). This LNS feature is input to an autoencoder NN-based detector for anomalous sound detection…”
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