Výsledky vyhľadávania - Deep autoencoder-based clustering

  1. 1

    Deep Convolutional Asymmetric Autoencoder-Based Spatial-Spectral Clustering Network for Hyperspectral Image Autor Liu, Baisen, Kong, Weili, Wang, Yan

    ISSN: 1530-8669, 1530-8677
    Vydavateľské údaje: Oxford Hindawi 2022
    “… In this paper, we propose a novel deep convolutional asymmetric autoencoder-based spatial-spectral clustering network (DCAAES2C-Net…”
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  2. 2

    Matrix Factorization and Deep Autoencoder based Clustering Scheme for Large-scale UAV Networks Autor Fang, Jiaolan, Wang, Chan, Li, Rongpeng, Wei, Hanyu, Zhao, Minjian

    ISSN: 2577-2465
    Vydavateľské údaje: IEEE 01.06.2023
    Vydané v IEEE Vehicular Technology Conference (01.06.2023)
    “… Typically, clustering is widely adopted to reduce the degradation of network performance in large-scale UAV networks…”
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    Konferenčný príspevok..
  3. 3

    An autoencoder-based deep learning approach for clustering time series data Autor Tavakoli, Neda, Siami-Namini, Sima, Adl Khanghah, Mahdi, Mirza Soltani, Fahimeh, Siami Namin, Akbar

    ISSN: 2523-3963, 2523-3971
    Vydavateľské údaje: Cham Springer International Publishing 01.05.2020
    Vydané v SN applied sciences (01.05.2020)
    “… Second, an autoencoder-based deep learning model is built to model both known and hidden non-linear features of time series data…”
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  4. 4

    DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning Autor Lu, Si, Li, Ruisi

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 15.02.2021
    Vydané v arXiv.org (15.02.2021)
    “… When those assumptions does not hold, these algorithms then might not work. In this paper, we propose DAC, Deep Autoencoder-based Clustering, a generalized data-driven framework to learn clustering representations using deep neuron networks…”
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  5. 5

    Operationalization of the construct “Business model of a Bank”: clustering analyses with deep neural networks Autor Herdt, Manfred, Schulte-Mattler, Hermann

    ISSN: 1750-2071, 1745-6452, 1750-2071
    Vydavateľské údaje: London Palgrave Macmillan 01.09.2025
    Vydané v Journal of banking regulation (01.09.2025)
    “…This paper presents a framework to operationalize the multidimensional construct of a bank's business model (BBM). We conceptualize the construct from a…”
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  6. 6

    A Robust PCA Feature Selection To Assist Deep Clustering Autoencoder-Based Network Anomaly Detection Autor Nguyen, Van Quan, Nguyen, Viet Hung, Cao, Van Loi, Khac, Nhien - An Le, Shone, Nathan

    Vydavateľské údaje: IEEE 21.12.2021
    “…This paper presents a novel method to enhance the performance of Clustering-based Autoencoder models for network anomaly detection…”
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  7. 7

    Antenna Scanning Type Classification with Autoencoder Based Deep Clustering Autor Ozmen, Emirhan, Ozkazanc, Yakup

    Vydavateľské údaje: IEEE 09.06.2021
    “…In this study, a deep learning-based algorithm is proposed for automatic detection of antenna scanning types used in EW systems…”
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  8. 8

    A Novel Autoencoder based Federated Deep Transfer Learning and Weighted k-Subspace Network clustering for Intelligent Intrusion Detection for the Internet of Things Autor Lavanya, V. S., Anushiya, R.

    ISSN: 2953-4860
    Vydavateľské údaje: 2024
    “… In this research, suggest an Autoencoder based Deep Federated Transfer Learning (ADFTL) to conquer these obstacles…”
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  9. 9

    Brain tumor classification using a hybrid deep autoencoder with Bayesian fuzzy clustering-based segmentation approach Autor Siva Raja, P.M., rani, Antony Viswasa

    ISSN: 0208-5216
    Vydavateľské údaje: Elsevier B.V 01.01.2020
    “… This paper developed a brain tumor classification using a hybrid deep autoencoder with a Bayesian fuzzy clustering-based segmentation approach…”
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    Leveraging tensor kernels to reduce objective function mismatch in deep clustering Autor Trosten, Daniel J., Løkse, Sigurd, Jenssen, Robert, Kampffmeyer, Michael

    ISSN: 0031-3203, 1873-5142
    Vydavateľské údaje: Elsevier Ltd 01.05.2024
    Vydané v Pattern recognition (01.05.2024)
    “… In this work we study OFM in deep clustering, and find that the popular autoencoder-based approach to deep clustering can lead to both reduced clustering performance, and a significant amount of OFM…”
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  11. 11

    Clustering Time Series Data through Autoencoder-based Deep Learning Models Autor Tavakoli, Neda, Siami-Namini, Sima, Mahdi Adl Khanghah, Fahimeh Mirza Soltani, Namin, Akbar Siami

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 11.04.2020
    Vydané v arXiv.org (11.04.2020)
    “…). In particular, deep learning techniques are capable of capturing and learning hidden features in a given data sets and thus building a more accurate prediction model for clustering and labeling problem…”
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  12. 12

    scTPC: a novel semisupervised deep clustering model for scRNA-seq data Autor Qiu, Yushan, Yang, Lingfei, Jiang, Hao, Zou, Quan

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Vydavateľské údaje: England Oxford University Press 02.05.2024
    Vydané v Bioinformatics (Oxford, England) (02.05.2024)
    “… Results This study investigates a semisupervised clustering model called scTPC, which integrates the triplet constraint, pairwise constraint, and cross-entropy constraint based on deep learning…”
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  13. 13

    Unsupervised Seismic Facies Deep Clustering Via Lognormal Mixture-Based Variational Autoencoder Autor Hua, Haowei, Qian, Feng, Zhang, Gulan, Yue, Yuehua

    ISSN: 1939-1404, 2151-1535
    Vydavateľské údaje: Piscataway IEEE 2023
    “… The dominant isolated learning-based SFA schemes have gained considerable attention and primarily focus on learning the best representation of prestack data and generating facies maps by clustering…”
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  14. 14

    Autoencoder-based unsupervised clustering and hashing Autor Zhang, Bolin, Qian, Jiangbo

    ISSN: 0924-669X, 1573-7497
    Vydavateľské údaje: New York Springer US 01.01.2021
    “…Faced with a large amount of data and high-dimensional data information in a database, the existing exact nearest neighbor retrieval methods cannot obtain…”
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  15. 15

    A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis Autor Ellis, Charles A., Miller, Robyn L., Calhoun, Vince D.

    ISSN: 2694-0604, 2694-0604
    Vydavateľské údaje: United States IEEE 01.01.2023
    “… learning-based approaches with automated feature learning to cluster EEG. Those studies involve separately training an autoencoder and then performing clustering…”
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    Konferenčný príspevok.. Journal Article
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    A New Graph Autoencoder-Based Multi-Level Kernel Subspace Fusion Framework for Single-Cell Type Identification Autor Wang, Juan, Qiao, Tian-Jing, Zheng, Chun-Hou, Liu, Jin-Xing, Shang, Jun-Liang

    ISSN: 1545-5963, 1557-9964, 1557-9964
    Vydavateľské údaje: United States IEEE 01.11.2024
    “… Although many single-cell clustering methods have been developed recently, few can fully exploit the deep potential relationships between cells, resulting in suboptimal clustering…”
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  17. 17

    Achieving deep clustering through the use of variational autoencoders and similarity-based loss Autor Ma, He

    ISSN: 1551-0018, 1551-0018
    Vydavateľské údaje: AIMS Press 01.01.2022
    “… In this work, a novel variational autoencoder-based deep clustering algorithm is proposed. It treats the Gaussian mixture model as the prior latent space and uses…”
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    Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry Autor Zhang, Zunming, Chen, Xinyu, Tang, Rui, Zhu, Yuxuan, Guo, Han, Qu, Yunjia, Xie, Pengtao, Lian, Ian Y., Wang, Yingxiao, Lo, Yu-Hwa

    ISSN: 2045-2322, 2045-2322
    Vydavateľské údaje: London Nature Publishing Group UK 23.11.2023
    Vydané v Scientific reports (23.11.2023)
    “… We present an unsupervised deep embedding algorithm, the Deep Convolutional Autoencoder-based Clustering (DCAEC…”
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  19. 19

    Patient Clustering for Vital Organ Failure Using ICD Code With Graph Attention Autor Liu, Zhangdaihong, Hu, Ying, Wu, Xuan, Mertes, Gert, Yang, Yang, Clifton, David A.

    ISSN: 0018-9294, 1558-2531, 1558-2531
    Vydavateľské údaje: United States IEEE 01.08.2023
    “… We employ an autoencoder-based deep clustering architecture jointly trained with a K-means loss, and a non-linear dimension reduction is performed to obtain patient clusters on the MIMIC-III dataset. Results…”
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    scCompressSA: dual-channel self-attention based deep autoencoder model for single-cell clustering by compressing gene–gene interactions Autor Zhang, Wei, Yu, Ruochen, Xu, Zeqi, Li, Junnan, Gao, Wenhao, Jiang, Mingfeng, Dai, Qi

    ISSN: 1471-2164, 1471-2164
    Vydavateľské údaje: London BioMed Central 29.04.2024
    Vydané v BMC genomics (29.04.2024)
    “…Background Single-cell clustering has played an important role in exploring the molecular mechanisms about cell differentiation and human diseases…”
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