Search Results - Semi-supervised autoencoder

Semi‐supervised deep autoencoder for seismic facies classification by Liu, Xingye, Li, Bin, Li, Jingye, Chen, Xiaohong, Li, Qingchun, Chen, Yangkang

“…‐supervised deep autoencoder by taking the mean of intra‐class and the whole population of facies into account to construct a classification regularization term, thereby improving the classification accuracy…”
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Synthetic Aperture Local Conformal Autoencoder for Semi-Supervised Speaker's DOA Tracking by Cohen, Idan, Gannot, Sharon, Lindenbaum, Ofir

“… We aim to achieve this in real-time, using as few measurements as possible. Toward this goal, we present a semi-supervised learning scheme that tracks the speaker using acoustic features…”
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Fault diagnosis of power equipment based on variational autoencoder and semi‐supervised learning by Ye, Bo, Li, Feng, Zhang, Linghao, Chang, Zhengwei, Wang, Bin, Zhang, Xiaoyu, Bodanbai, Sayina

“…) method based on variational autoencoder and semi‐supervised learning is proposed in this paper…”
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A semi-supervised autoencoder for autism disease diagnosis by Yin, Wutao, Li, Longhai, Wu, Fang-Xiang

“… In this paper, we proposed a semi-supervised autoencoder (AE) for autism diagnosis using functional connectivity (FC…”
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Improved semi-supervised autoencoder for deception detection by Fu, Hongliang, Lei, Peizhi, Tao, Huawei, Zhao, Li, Yang, Jing

“… To solve this problem, this paper proposes a semi-supervised additive noise autoencoder model for deception detection…”
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Semi-Supervised Autoencoder for Chemical Gas Classification with FTIR Spectrum by Jang, Hee-Deok, Kwon, Seokjoon, Nam, Hyunwoo, Chang, Dong Eui

“… In this paper, we propose a deep neural network utilizing a semi-supervised autoencoder (SSAE) for the classification of chemical gases based on FTIR spectra…”
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Stacked Autoencoders Driven by Semi-Supervised Learning for Building Extraction from near Infrared Remote Sensing Imagery by Protopapadakis, Eftychios, Doulamis, Anastasios, Doulamis, Nikolaos, Maltezos, Evangelos

“…In this paper, we propose a Stack Auto-encoder (SAE)-Driven and Semi-Supervised (SSL)-Based Deep Neural Network…”
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A Semi-Supervised Autoencoder-Based Approach for Protein Function Prediction by Dhanuka, Richa, Tripathi, Anushree, Singh, Jyoti P.

“… A set of autoencoders is trained in a semi-supervised manner with protein sequences. Each autoencoder corresponds to a single protein function…”
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A hybrid classification autoencoder for semi-supervised fault diagnosis in rotating machinery by Wu, Xinya, Zhang, Yan, Cheng, Changming, Peng, Zhike

“…•A novel semi-supervised fault diagnosis method is proposed.•The model can be trained using both labeled and unlabeled data simultaneously…”
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scSSA: A clustering method for single cell RNA-seq data based on semi-supervised autoencoder by Zhao, Jian-Ping, Hou, Tong-Shuai, Su, Yansen, Zheng, Chun-Hou

“…•In this study, We proposed to use semi-supervised autoencoder to reduce the dimension of data, because it makes good use of some existing label information…”
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A semi-supervised autoencoder framework for joint generation and classification of breathing by Pastor-Serrano, Oscar, Lathouwers, Danny, Perkó, Zoltán

“…•A novel semi-supervised algorithm based on Adversarial Autoencoders that allows joint classification and generation of breathing…”
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Stacked semi-supervised autoencoder-regularized RVFLNs for reliable prediction of molten iron quality in blast furnace by Zhou, Ping, Zhao, Peng, Ou, Zihui, Chai, Tianyou

“…This paper proposes a novel stacked semi-supervised autoencoder-regularized random vector functional-link networks (RVFLNs…”
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Mental workload recognition from EEG signals via semi-supervised autoencoders by Liu, Qi, Jiang, Xu, Wang, Huanjie, Chen, Jingjing

“… To address this, we propose semi-supervised autoencoders that combine labeled and abundant unlabeled data…”
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Explaining anomalies through semi-supervised Autoencoders by Angiulli, Fabrizio, Fassetti, Fabio, Ferragina, Luca, Nisticò, Simona

“…://github.com/AIDALab-DIMES/AE-XAD. (for AutoEncoder-based eXplainable Anomaly Detection), extends a recently introduced semi-supervised variant of the Autoencoder architecture…”
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Customization of latent space in semi-supervised Variational AutoEncoder by An, Seunghwan, Jeon, Jong-June

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Tibetan Sentiment Classification Method Based on Semi-Supervised Recursive Autoencoders by Yan, Xiaodong, Song, Wei, Zhao, Xiaobing, Wang, Anti

“…We apply the semi-supervised recursive autoencoders (RAE) model for the sentiment classification task of Tibetan short text, and we obtain a better classification effect…”
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A fingerprint technique for indoor localization using autoencoder based semi-supervised deep extreme learning machine by Ezzati Khatab, Zahra, Hajihoseini Gazestani, Amirhosein, Ghorashi, Seyed Ali, Ghavami, Mohammad

“…•Using unlabeled data to encourage more participant in crowd-sensing process.•Decreasing the complexity and improving the accuracy.•Real test in addition to…”
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Self-Supervised Learning Meets Custom Autoencoder Classifier: A Semi-Supervised Approach for Encrypted Traffic Anomaly Detection by Ramzi Bahlali, A., Bachir, Abdelmalik, Labed, Abdeldjalil

“… In this paper, we propose a semi-supervised learning framework that leverages Self-Supervised Learning (SSL…”
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SeGMA: Semi-Supervised Gaussian Mixture Autoencoder by Smieja, Marek, Wolczyk, Maciej, Tabor, Jacek, Geiger, Bernhard C.

“…We propose a semi-supervised generative model, SeGMA, which learns a joint probability distribution of data and their classes and is implemented in a typical Wasserstein autoencoder framework…”
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Exploring semi-supervised variational autoencoders for biomedical relation extraction by Zhang, Yijia, Lu, Zhiyong

“…•A semi-supervised method is proposed based on variational autoencoders (VAE) for biomedical relation extraction…”
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