Comparing Vision Transformers and Convolutional Neural Networks for Image Classification: A Literature Review
José Maurício, Inês Domingues, Jorge Bernardino
2023 · Applied Sciences · 546 citations
Transformers are models that implement a mechanism of self-attention, individually weighting the importance of each part of the input data. Their use in image classification tasks is still somewhat limited since researchers have so far chosen Convolutional Neural Networks for image classification and transformers were more targeted to Natural Language Processing (NLP) tasks. Therefore, this paper presents a literature review that shows the differences between Vision Transformers (ViT) and Convolutional Neural Networks. The state of the art that used the two architectures for image classificat…
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