ScholarGate
Msaidizi
Machine learningDeep learning / NLP / CV

Transformer wa Maono unaojifundisha

Transformer wa Maono unaojifundisha (SSL-ViT) hutumia malengo ya mafunzo ya awali yanayojifundisha — kama vile utabiri wa kiraka kilichofichwa (MAE) au kujifundisha bila lebo (DINO) — kwa usanifu wa Transformer wa Maono, kuwezesha uwakilishi wenye nguvu wa kuona kujifunzwa kutoka kwa makusanyo makubwa ya picha zisizo na lebo kabla ya marekebisho yoyote maalum ya kazi.

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Vyanzo

  1. Caron, M., Touvron, H., Misra, I., Jegou, H., Mairal, J., Bojanowski, P., & Joulin, A. (2021). Emerging Properties in Self-Supervised Vision Transformers. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 9650–9660. link
  2. He, K., Chen, X., Xie, S., Li, Y., Dollar, P., & Girshick, R. (2022). Masked Autoencoders Are Scalable Vision Learners. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 16000–16009. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Self-supervised Vision Transformer (SSL-ViT). ScholarGate. https://scholargate.app/sw/deep-learning/self-supervised-vision-transformer

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Imerejelewa na

ScholarGateSelf-supervised Vision Transformer (Self-supervised Vision Transformer (SSL-ViT)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/self-supervised-vision-transformer · Seti ya data: https://doi.org/10.5281/zenodo.20539026