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IEEE/ICACT20240345 Slide.09        [Big Slide]	Oral Presentation
	Vision Transformer Architecture Vision Transformers (ViTs) are deep learning models designed for computer vision tasks. The model architecture includes a self-attention mechanism that captures relationships between different parts of an image. The ViT model used a 16x16 patch size, generating 16,384 patches for a single input image of size 2048x2048. The patch images were tokenized and flattened, and a linear projection layer transformed them into lower-dimensional vectors for further processing.

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