Machine learningDeep learning / NLP / CV

Polunadzirana detekcija objekata

Polunadzirana detekcija objekata obučava detektor na malom skupu označenih slika i velikom skupu neoznačenih slika. Model učitelja generiše pseudo-oznake za neoznačene slike, a model učenika uči iz stvarnih i pseudo-označenih podataka, dramatično smanjujući skupo ručno anotiranje graničnih kutija, dok postiže tačnost konkurentnu potpuno nadziranim baznim linijama.

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Izvori

  1. Sohn, K., Zhang, Z., Li, C.-L., Zhang, H., Lee, C.-Y., & Pfister, T. (2020). A Simple Semi-Supervised Learning Framework for Object Detection. arXiv preprint arXiv:2005.04757. link
  2. Liu, Y.-C., Ma, C.-Y., He, Z., Kuo, C.-W., Chen, K., Zhang, P., Wu, B., Kira, Z., & Vajda, P. (2021). Unbiased Teacher for Semi-Supervised Object Detection. ICLR 2021. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Semi-supervised Object Detection (Pseudo-label / Mean-Teacher Paradigm). ScholarGate. https://scholargate.app/sr/deep-learning/semi-supervised-object-detection

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Citirana u

ScholarGateSemi-supervised Object Detection (Semi-supervised Object Detection (Pseudo-label / Mean-Teacher Paradigm)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/deep-learning/semi-supervised-object-detection · Skup podataka: https://doi.org/10.5281/zenodo.20539026