Auflistung nach Schlagwort "Domain adaptation"

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  • Adversarial discriminative domain adaptation for deforestation detection 
    Noa, J.; Soto, P.J.; Costa, G.A.O.P.; Wittich, D.; Feitosa, R.Q.; Rottensteiner, F. (Katlenburg-Lindau : Copernicus, 2021)
    Although very efficient in a number of application fields, deep learning based models are known to demand large amounts of labeled data for training. Particularly for remote sensing applications, responding to that demand ...
  • Boosted unsupervised multi-source selection for domain adaptation 
    Vogt, Karsten; Paul, A.; Ostermann, Jörn; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2017)
    Supervised machine learning needs high quality, densely sampled and labelled training data. Transfer learning (TL) techniques have been devised to reduce this dependency by adapting classifiers trained on different, but ...
  • A comparison of two strategies for avoiding negative transfer in domain adaptation based on logistic regression 
    Paul, A.; Vogt, K.; Rottensteiner, F.; Ostermann, J.; Heipke, C. (Göttingen : Copernicus GmbH, 2018)
    In this paper we deal with the problem of measuring the similarity between training and tests datasets in the context of transfer learning (TL) for image classification. TL tries to transfer knowledge from a source domain, ...
  • Domain adaptation based transfer learning approach for solving PDEs on complex geometries 
    Chakraborty, Ayan; Anitescu, Cosmin; Zhuang, Xiaoying; Rabczuk, Timon (London : Springer, 2022)
    In machine learning, if the training data is independently and identically distributed as the test data then a trained model can make an accurate predictions for new samples of data. Conventional machine learning has a ...
  • Statistical alignment in transfer learning to address the repair problem: An experimental case study 
    Wickramarachchi, Chandula T. (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2023-01-26)
    Repair is a critical step in maintenance of civil structures to ensure safe operation. However, repair can pose a problem for data-driven approaches of long-term structural health monitoring, because repairs can change the ...
  • Transfer learning based on logistic regression 
    Paul, Andreas; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)
    In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for transductive transfer ...