Suchergebnisse - (( Autoencoder applications ) OR ( Autoencoder publications ))

  1. 1

    An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing von Shankar, Venkatesh, Parsana, Sohil

    ISSN: 0092-0703, 1552-7824
    Veröffentlicht: New York Springer US 01.11.2022
    Veröffentlicht in Journal of the Academy of Marketing Science (01.11.2022)
    “… ) models, have surged in popularity for analyzing unstructured data in marketing. Yet, we do not fully understand which NLP models are appropriate for which marketing applications and what insights can be best derived …”
    Volltext
    Journal Article
  2. 2

    Prediction of hysteretic matric potential dynamics using artificial intelligence: application of autoencoder neural networks von Aqel, Nedal, Reusser, Lea, Margreth, Stephan, Carminati, Andrea, Lehmann, Peter

    ISSN: 1991-9603, 1991-959X, 1991-962X, 1991-9603, 1991-962X
    Veröffentlicht: Katlenburg-Lindau Copernicus GmbH 18.09.2024
    Veröffentlicht in Geoscientific Model Development (18.09.2024)
    “… Information on soil water potential is essential to assessing the soil moisture state, to prevent soil compaction in weak soils, and to optimize crop …”
    Volltext
    Journal Article
  3. 3

    Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath von Soleymani, Farzan, Paquet, Eric

    ISSN: 0957-4174, 1873-6793
    Veröffentlicht: New York Elsevier Ltd 15.10.2020
    Veröffentlicht in Expert systems with applications (15.10.2020)
    “… •Extracting high-level features using restricted stacked autoencoder.•A convolutional neural network is employed to enforce the policy …”
    Volltext
    Journal Article
  4. 4

    Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study von Cha, Dongchul, Sung, MinDong, Park, Yu-Rang

    ISSN: 2291-9694, 2291-9694
    Veröffentlicht: Toronto JMIR Publications 01.06.2021
    Veröffentlicht in JMIR medical informatics (01.06.2021)
    “… Background: Machine learning (ML) is now widely deployed in our everyday lives. Building robust ML models requires a massive amount of data for training …”
    Volltext
    Journal Article
  5. 5

    Polytopic autoencoders with smooth clustering for reduced-order modeling of flows von Heiland, Jan, Kim, Yongho

    ISSN: 0021-9991
    Veröffentlicht: Elsevier Inc 15.01.2025
    Veröffentlicht in Journal of computational physics (15.01.2025)
    “… With the advancement of neural networks, there has been a notable increase, both in terms of quantity and variety, in research publications concerning the application of autoencoders to reduced-order models …”
    Volltext
    Journal Article
  6. 6

    RETRACTED: Pre-training graph autoencoder incorporating hierarchical topology knowledge von Zhu, Hongyin, Li, Yakun, Liu, Luyang, Tong, Haonan, Lin, Qunyang, Zhang, Chuang

    ISSN: 0957-4174
    Veröffentlicht: Elsevier Ltd 15.03.2025
    Veröffentlicht in Expert systems with applications (15.03.2025)
    “… Concerns were raised following the publication of the paper titled “Pre-training Graph Autoencoder Incorporating Hierarchical Topology Knowledge” (DOI: https://doi.org/10.1016/j.eswa.2024.125976 …”
    Volltext
    Journal Article
  7. 7

    Slow feature‐constrained decomposition autoencoder: Application to process anomaly detection and localization von Jia, Mingwei, Jiang, Lingwei, Hu, Junhao, Liu, Yi, Chen, Tao

    ISSN: 0890-6327, 1099-1115
    Veröffentlicht: Hoboken, USA John Wiley & Sons, Inc 01.07.2025
    “… To address this challenge, we propose a slow feature‐constrained decomposition autoencoder (SFC‐DAE …”
    Volltext
    Journal Article
  8. 8

    De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping von Sattarov, Boris, Baskin, Igor I, Horvath, Dragos, Marcou, Gilles, Bjerrum, Esben Jannik, Varnek, Alexandre

    ISSN: 1549-960X, 1549-960X
    Veröffentlicht: United States 25.03.2019
    Veröffentlicht in Journal of chemical information and modeling (25.03.2019)
    “… Here we show that Generative Topographic Mapping (GTM) can be used to explore the latent space of the SMILES-based autoencoders and generate focused molecular libraries of interest …”
    Weitere Angaben
    Journal Article
  9. 9

    Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology von Janowczyk, Andrew, Basavanhally, Ajay, Madabhushi, Anant

    ISSN: 0895-6111, 1879-0771, 1879-0771
    Veröffentlicht: United States Elsevier Ltd 01.04.2017
    Veröffentlicht in Computerized medical imaging and graphics (01.04.2017)
    “… •Stain Normalization using Sparse AutoEncoders (StaNoSA) in introduced.•It standardizes color distributions of a test image to a single template image …”
    Volltext
    Journal Article
  10. 10

    Optimizing Large Scale Problems With Metaheuristics in a Reduced Space Mapped by Autoencoders-Application to the Wind-Hydro Coordination von Miranda, Vladimiro, da Hora Martins, Joana, Palma, Vera

    ISSN: 0885-8950, 1558-0679
    Veröffentlicht: New York IEEE 01.11.2014
    Veröffentlicht in IEEE transactions on power systems (01.11.2014)
    “… The technique applies autoencoders as a reversible mapping between the original problem space and a reduced space …”
    Volltext
    Journal Article
  11. 11

    Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design von Mak, Hugo Wai Leung, Han, Runze, Yin, Hoover H. F.

    ISSN: 1424-8220, 1424-8220
    Veröffentlicht: Switzerland MDPI AG 25.03.2023
    Veröffentlicht in Sensors (Basel, Switzerland) (25.03.2023)
    “… In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction …”
    Volltext
    Journal Article
  12. 12

    A new investment method with AutoEncoder: Applications to crypto currencies von Nakano, Masafumi, Takahashi, Akihiko

    ISSN: 0957-4174, 1873-6793
    Veröffentlicht: New York Elsevier Ltd 30.12.2020
    Veröffentlicht in Expert systems with applications (30.12.2020)
    “… •AutoEncoder extracts the factors which enable to prevent the large drawdown.•The extracted non-linear factors are implemented by the dynamic delta hedging …”
    Volltext
    Journal Article
  13. 13

    Disentangled-Multimodal Adversarial Autoencoder: Application to Infant Age Prediction With Incomplete Multimodal Neuroimages von Hu, Dan, Zhang, Han, Wu, Zhengwang, Wang, Fan, Wang, Li, Smith, J. Keith, Lin, Weili, Li, Gang, Shen, Dinggang

    ISSN: 0278-0062, 1558-254X, 1558-254X
    Veröffentlicht: United States IEEE 01.12.2020
    Veröffentlicht in IEEE transactions on medical imaging (01.12.2020)
    “… Effective fusion of structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) data has the potential to boost the accuracy …”
    Volltext
    Journal Article
  14. 14

    Autoencoder-based feature extraction for the automatic detection of snow avalanches in seismic data von Simeon, Andri, Pérez-Guillén, Cristina, Volpi, Michele, Seupel, Christine, van Herwijnen, Alec

    ISSN: 1991-9603, 1991-959X, 1991-962X, 1991-9603, 1991-962X
    Veröffentlicht: Katlenburg-Lindau Copernicus GmbH 20.11.2025
    Veröffentlicht in Geoscientific Model Development (20.11.2025)
    “… Monitoring snow avalanche activity is essential for operational avalanche forecasting and the successful implementation of mitigation measures to ensure safety …”
    Volltext
    Journal Article
  15. 15

    A comprehensive survey on design and application of autoencoder in deep learning von Li, Pengzhi, Pei, Yan, Li, Jianqiang

    ISSN: 1568-4946, 1872-9681
    Veröffentlicht: Elsevier B.V 01.05.2023
    Veröffentlicht in Applied soft computing (01.05.2023)
    “… Researchers have proposed several improved versions of autoencoder based on different application fields …”
    Volltext
    Journal Article
  16. 16

    A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network von Wang, Lei, You, Zhu-Hong, Chen, Xing, Xia, Shi-Xiong, Liu, Feng, Yan, Xin, Zhou, Yong, Song, Ke-Jian

    ISSN: 1557-8666, 1557-8666
    Veröffentlicht: United States 01.03.2018
    Veröffentlicht in Journal of computational biology (01.03.2018)
    “… In this article, we propose a new computational method for predicting DTIs from drug molecular structure and protein sequence by using the stacked autoencoder of deep learning, which can adequately …”
    Weitere Angaben
    Journal Article
  17. 17

    Development of a novel parallel framework upon deep dual‐enhanced autoencoder and its applications for industrial soft sensing von Chen, Xu, Shao, Weiming, Wei, Chihang

    ISSN: 0008-4034, 1939-019X
    Veröffentlicht: 22.07.2025
    Veröffentlicht in Canadian journal of chemical engineering (22.07.2025)
    “… In recent years, data‐driven soft sensing technology has provided a cost‐effective support for industrial process monitoring, in which autoencoder plays an important role in extracting features for soft sensing technology …”
    Volltext
    Journal Article
  18. 18

    SDCA: a novel stack deep convolutional autoencoder – an application on retinal image denoising von Ghosh, Swarup Kr, Biswas, Biswajit, Ghosh, Anupam

    ISSN: 1751-9659, 1751-9667
    Veröffentlicht: The Institution of Engineering and Technology 12.12.2019
    Veröffentlicht in IET image processing (12.12.2019)
    “… This study represents a deep learning based approach to denoising images and restoring features using stack denoising convolutional autoencoder …”
    Volltext
    Journal Article
  19. 19

    Recent Research and Applications in Variational Autoencoders for Industrial Prognosis and Health Management: A Survey von Zemouri, Ryad, Levesque, Melanie, Boucher, Etienne, Kirouac, Mathieu, Lafleur, Francois, Bernier, Simon, Merkhouf, Arezki

    ISSN: 2166-5656
    Veröffentlicht: IEEE 01.05.2022
    Veröffentlicht in Prognostics and System Health Management Conference (01.05.2022)
    “… The common particularity of all these application domains is that a great part of this data is mostly unlabeled …”
    Volltext
    Tagungsbericht
  20. 20

    1D-CONVOLUTIONAL AUTOENCODER BASED HYPERSPECTRAL DATA COMPRESSION von Kuester, J., Gross, W., Middelmann, W.

    ISSN: 2194-9034, 1682-1750, 2194-9034
    Veröffentlicht: Gottingen Copernicus GmbH 28.06.2021
    “… Hyperspectral sensor technology has been advancing in recent years and become more practical to tackle a variety of applications …”
    Volltext
    Journal Article Tagungsbericht