Machine learning

EfficientNet

EfficientNet je obitelj arhitektura konvolucijskih neuronskih mreža koju su predstavili Mingxing Tan i Quoc V. Le (Google Brain) na konferenciji ICML 2019. Sustavno skalira dubinu, širinu i ulaznu rezoluciju mreže koristeći jedinstveni složeni koeficijent, postižući najsuvremeniju točnost klasifikacije slika s znatno manje parametara i FLOP-ova od prethodnih mreža kao što su ResNet i Inception.

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Izvori

  1. Tan, M. & Le, Q. V. (2019). EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. Proceedings of the 36th International Conference on Machine Learning (ICML 2019), PMLR 97, 6105–6114. link
  2. Goodfellow, I., Bengio, Y. & Courville, A. (2016). Deep Learning. MIT Press. ISBN: 978-0-262-03561-3

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. ScholarGate. https://scholargate.app/hr/deep-learning/efficientnet

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Citirana u

ScholarGateEfficientNet (EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks). Preuzeto 2026-06-15 s https://scholargate.app/hr/deep-learning/efficientnet · Skup podataka: https://doi.org/10.5281/zenodo.20539026