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Machine learningDeep learning / NLP / CV

Ugawaji wa Kisemantiki wa Nusu-Usimamizi

Ugawaji wa kisemantiki wa nusu-usimamizi hufunza mifumo ya uwekaji lebo ya kiwango cha pikseli kwa kutumia seti ndogo ya picha zenye lebo kamili zikichanganywa na seti kubwa zaidi ya picha zisizo na lebo. Mbinu kama vile uwekaji lebo bandia (pseudo-labeling) na udhibiti wa uthabiti hutoa ishara ya usimamizi kutoka kwa data isiyo na lebo, na kufanya iwezekane kufikia usahihi karibu na ule wa usimamizi kamili kwa gharama ndogo ya uwekaji lebo.

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Vyanzo

  1. Ouali, Y., Hudelot, C., & Tami, M. (2020). Semi-Supervised Semantic Segmentation with Cross-Consistency Training. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 12674–12684. DOI: 10.1109/CVPR42600.2020.01269
  2. Zou, Y., Zhang, Z., Zhang, H., Li, C.-L., Bian, X., Huang, J.-B., & Pfister, T. (2020). PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. International Conference on Learning Representations (ICLR 2021). link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Semi-supervised Semantic Segmentation (Pseudo-label and Consistency-based). ScholarGate. https://scholargate.app/sw/deep-learning/semi-supervised-semantic-segmentation

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ScholarGateSemi-supervised Semantic Segmentation (Semi-supervised Semantic Segmentation (Pseudo-label and Consistency-based)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/semi-supervised-semantic-segmentation · Seti ya data: https://doi.org/10.5281/zenodo.20539026