Computer Science and Engineering Deep Learning Virtual Laboratory Experiments

Transformers in Vision

References

  1. A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, and N. Houlsby, "An Image is Worth 16×16 Words: Transformers for Image Recognition at Scale," in Proceedings of the International Conference on Learning Representations (ICLR), 2021. [arXiv:2010.11929]
  2. A. Krizhevsky, "Learning Multiple Layers of Features from Tiny Images," Technical Report, University of Toronto, 2009. Available at: https://www.cs.toronto.edu/~kriz/cifar.html
  3. A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, "Attention Is All You Need," in Advances in Neural Information Processing Systems (NeurIPS), vol. 30, 2017. [arXiv:1706.03762]