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Machine learningDeep learning / NLP / CV

Klasifikasi Imej Berbantukan Kelemahan

Klasifikasi imej terbantu kelemahan melatih rangkaian berasaskan konvolusional atau transformer menggunakan hanya penyeliaan yang kasar, tidak lengkap, atau berisiko — seperti label kategori peringkat imej, hashtag, atau tag yang dikikis dari web — tanpa memerlukan kotak sempadan yang tepat atau anotasi piksel. Ini secara dramatik mengurangkan kos pelabelan sambil masih membolehkan pengecaman visual berketepatan tinggi pada skala.

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Sumber

  1. Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., & Torralba, A. (2016). Learning Deep Features for Discriminative Localization. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2921–2929. DOI: 10.1109/CVPR.2016.319
  2. Mahajan, D., Girshick, R., Ramanathan, V., He, K., Paluri, M., Li, Y., Bharambe, A., & van der Maaten, L. (2018). Exploring the Limits of Weakly Supervised Pretraining. Proceedings of the European Conference on Computer Vision (ECCV), 181–196. DOI: 10.1007/978-3-030-01216-8_12

Cara memetik halaman ini

ScholarGate. (2026, June 3). Weakly Supervised Image Classification (WSL-IC). ScholarGate. https://scholargate.app/ms/deep-learning/weakly-supervised-image-classification

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ScholarGateWeakly Supervised Image Classification (Weakly Supervised Image Classification (WSL-IC)). Dicapai 2026-06-15 daripada https://scholargate.app/ms/deep-learning/weakly-supervised-image-classification · Set data: https://doi.org/10.5281/zenodo.20539026