Vision Transformers (ViT) have emerged as a revolutionary approach in the field of computer vision. They capture global dependencies and long-range interactions within an image. This leads to remarkable performance improvements in various computer vision tasks, including image classification, object detection, and image generation.
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Table of contents
IntroductionTable of contentsNeural NetworksTransformersAttention Mechanism in Computer Vision (CV)Patch-based ProcessingPre-trained ModelsPython Snippet: Pre-trained ModelInterpretabilityHybrid ArchitecturesComparison with Other TechniquesAdvantagesApplicationLimitationsConclusionSort: