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Machine learningDeep learning / NLP / CV

Convolutional Neural Network Iliyoendeshwa kwa Kina

Kurekebisha CNN kwa kina kunamaanisha kuanza na mtandao ambao tayari ume fundishwa kwa seti kubwa ya data — kwa kawaida ImageNet — na kuendeleza mafunzo kwenye seti ndogo ya data lengwa ili mfumo ujizoeshe vipengele vya kuona vilivyojifunza kwa kazi mpya. Mbinu hii inapunguza sana data na hesabu zinazohitajika kufikia utendaji mzuri ikilinganishwa na kufundisha kuanzia mwanzo.

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Vyanzo

  1. Yosinski, J., Clune, J., Bengio, Y., & Lipson, H. (2014). How transferable are features in deep neural networks? Advances in Neural Information Processing Systems, 27. link
  2. Tajbakhsh, N., Shin, J. Y., Gurudu, S. R., Hurst, R. T., Kendall, C. B., Gotway, M. B., & Liang, J. (2016). Convolutional neural networks for medical image analysis: Full training or fine tuning? IEEE Transactions on Medical Imaging, 35(5), 1299–1312. DOI: 10.1109/TMI.2016.2535302

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Fine-Tuned Convolutional Neural Network (CNN Fine-Tuning via Transfer Learning). ScholarGate. https://scholargate.app/sw/deep-learning/fine-tuned-convolutional-neural-network

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ScholarGateFine-Tuned Convolutional Neural Network (Fine-Tuned Convolutional Neural Network (CNN Fine-Tuning via Transfer Learning)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/fine-tuned-convolutional-neural-network · Seti ya data: https://doi.org/10.5281/zenodo.20539026