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Machine learningDeep learning / NLP / CV

Transformer Multimodus

Transformer Multimodus ialah lanjutan kepada seni bina Transformer standard untuk memproses dan menalar secara bersama ke atas dua atau lebih modaliti input — paling lazimnya teks dan imej, tetapi juga audio, video, atau data berstruktur. Lapisan perhatian silang modaliti membenarkan maklumat daripada satu modaliti memaklumkan perwakilan dalam modaliti lain, membolehkan tugasan seperti menjawab persoalan visual, penjanaan kapsyen imej, dan analisis sentimen multimodus.

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Sumber

  1. Lu, J., Batra, D., Parikh, D., & Lee, S. (2019). ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks. Advances in Neural Information Processing Systems (NeurIPS), 32. link
  2. Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., ... & Sutskever, I. (2021). Learning Transferable Visual Models From Natural Language Supervision. Proceedings of the 38th International Conference on Machine Learning (ICML), PMLR 139. link

Cara memetik halaman ini

ScholarGate. (2026, June 3). Multimodal Transformer (Cross-Modal Attention-Based Architecture). ScholarGate. https://scholargate.app/ms/deep-learning/multimodal-transformer

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ScholarGateMultimodal Transformer (Multimodal Transformer (Cross-Modal Attention-Based Architecture)). Dicapai 2026-06-15 daripada https://scholargate.app/ms/deep-learning/multimodal-transformer · Set data: https://doi.org/10.5281/zenodo.20539026