Vision Transformers - The Future of Computer Vision!
Are you curious about how machines can understand and interpret images just like humans? In this video, we dive into the world of Vision Transformers (ViT) and explore how they're revolutionizing computer vision.
Traditionally, Convolutional Neural Networks (CNNs) have been the backbone of image recognition tasks. However, the Vision Transformer is a groundbreaking innovation that uses a self-attention mechanism to understand images in a completely new way. By treating image patches like words in a sentence, the ViT learns complex patterns and relationships, allowing it to analyze images with unprecedented accuracy and efficiency.
What you’ll learn in this video:
The basics of Convolutional Neural Networks (CNNs) and their limitations.
How Transformers, originally designed for text, have been adapted for visual tasks.
The unique way Vision Transformers analyze images using self-attention.
The advantages of Vision Transformers over traditional CNNs in computer vision tasks.
Join us as we unpack the science behind Vision Transformers and discover why they're considered a game-changer in the field of AI and machine learning!
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