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Višeslojni perceptron sa finim podešavanjem

Višeslojni perceptron sa finim podešavanjem (Fine-Tuned Multilayer Perceptron) polazi od težina naučenih na izvornom zadatku — ili na velikom skupu podataka opšte namene — i nastavlja obuku na manjem ciljnom skupu podataka sa smanjenom brzinom učenja. Ponovna upotreba prethodno naučenih reprezentacija omogućava MLP-u da brže konvergira i bolje generalizuje nego obuka od nule, naročito kada su označeni ciljni podaci oskudni.

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Izvori

  1. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323, 533–536. DOI: 10.1038/323533a0
  2. Yosinski, J., Clune, J., Bengio, Y., & Lipson, H. (2014). How transferable are features in deep neural networks? Advances in Neural Information Processing Systems, 27, 3320–3328. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Fine-Tuned Multilayer Perceptron (Transfer Learning via MLP Weight Adaptation). ScholarGate. https://scholargate.app/sr/deep-learning/fine-tuned-multilayer-perceptron

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Citirana u

ScholarGateFine-Tuned Multilayer Perceptron (Fine-Tuned Multilayer Perceptron (Transfer Learning via MLP Weight Adaptation)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/deep-learning/fine-tuned-multilayer-perceptron · Skup podataka: https://doi.org/10.5281/zenodo.20539026