Deep Learning, Computer Vision, Cnn, Transformers, AI.
self-attention mechanisms to model long-range dependencies and learn meaningful visual features. How ViTs Work: Image Patching: The input image is divided into non-overlapping patches, typically of equal size, such as 16x16 or 32x32 pixels. Each patch is then reshaped into a 1D vector. Embedding: