Transformers in Computer Vision

Transformers in Computer Vision

What you’ll learn

  • What are transformer networks?
  • State of the Art architectures for CV Apps like Image Classification, Semantic Segmentation, Object Detection and Video Processing
  • Practical application of SoTA architectures like ViT, DETR, SWIN in Huggingface vision transformers
  • Attention mechanisms as a general Deep Learning idea
  • Inductive Bias and the landscape of DL models in terms of modeling assumptions
  • Transformers application in NLP and Machine Translation
  • Transformers in Computer Vision
  • Different types of attention in Computer Vision

How to Enroll Transformers in Computer Vision course?

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