Self-supervised GAN
Self-supervised GAN memperkaya Generative Adversarial Network (GAN) standar dengan satu atau lebih tugas bantu swa-awasi (self-supervised) — seperti memprediksi rotasi gambar atau posisi tambalan (patch) — yang menstabilkan pelatihan adversarial dan menghasilkan diskriminator yang mempelajari representasi kaya dan dapat ditransfer dari data tak berlabel tanpa memerlukan anotasi manual.
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Method map
The neighbourhood of related methods — select a node to explore.
Sumber
- Chen, T., Zhai, X., Ritter, M., Lucic, M., & Houlsby, N. (2019). Self-Supervised GANs via Auxiliary Rotation Loss. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 12154–12163. link ↗
- Liu, X., Zhang, F., Hou, Z., Mian, L., Wang, Z., Zhang, J., & Tang, J. (2021). Self-supervised learning: Generative or contrastive. IEEE Transactions on Knowledge and Data Engineering, 35(1), 857–876. DOI: 10.1109/TKDE.2021.3090866 ↗
Cara menyitasi halaman ini
ScholarGate. (2026, June 3). Self-supervised Generative Adversarial Network. ScholarGate. https://scholargate.app/id/deep-learning/self-supervised-gan
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Jaringan Adversarial GeneratifPembelajaran Mendalam↔ compare
- Jaringan Saraf Konvolusional SwadayaPembelajaran Mendalam↔ compare
- Variational Autoencoder Swadaya-TerawasiPembelajaran Mendalam↔ compare
- GAN Semi-terawasiPembelajaran Mendalam↔ compare
- Vision TransformerPembelajaran Mendalam↔ compare
Dirujuk oleh
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