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Transfer Learning dengan Convolutional Neural Network

Transfer Learning dengan CNN menggunakan kembali jaringan saraf konvolusional yang telah dilatih pada kumpulan data besar — paling umum ImageNet — dan mengadaptasi detektor fiturnya yang telah dipelajari ke kumpulan data target baru, yang seringkali lebih kecil. Hal ini memungkinkan peneliti untuk mencapai kinerja pengenalan gambar yang kuat tanpa sumber daya komputasi dan data besar yang diperlukan untuk melatih CNN dari awal.

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Sumber

  1. Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345–1359. DOI: 10.1109/TKDE.2009.191
  2. Yosinski, J., Clune, J., Bengio, Y., & Lipson, H. (2014). How transferable are features in deep neural networks? Advances in Neural Information Processing Systems (NeurIPS), 27, 3320–3328. link

Cara menyitasi halaman ini

ScholarGate. (2026, June 3). Transfer Learning with Convolutional Neural Network (Feature Extraction and Fine-Tuning). ScholarGate. https://scholargate.app/id/deep-learning/transfer-learning-with-convolutional-neural-network

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ScholarGateTransfer Learning with Convolutional Neural Network (Transfer Learning with Convolutional Neural Network (Feature Extraction and Fine-Tuning)). Diakses 2026-06-15 dari https://scholargate.app/id/deep-learning/transfer-learning-with-convolutional-neural-network · Set data: https://doi.org/10.5281/zenodo.20539026