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Rein Bugnot

As seen in: Towards Data Science
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Articles

Vision Transformers (ViT) Explained: Are They Better Than CNNs?

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By Rein Bugnot, Shreya Rao, Christabelle Pabalan, Pranay Dave
| Towards Data Science
Ever since the introduction of the self-attention mechanism, Transformers have been the top choice when it comes to Natural Language Processing (NLP) tasks. Self-attention-based models are highly parallelizable and require substantially fewer parameters, making them much more computationally efficient, less prone to overfitting, and easier to fine-tune for domain-specific tasks [1].
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