Bibliography (7):

1. CLIP: Connecting Text and Images: We’re introducing a neural network called CLIP which efficiently learns visual concepts from natural language supervision. CLIP can be applied to any visual classification benchmark by simply providing the names of the visual categories to be recognized, similar to the ‘zero-shot’ capabilities of GPT-2 and GPT-3

2. ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

3. BASIC: Combined Scaling for Open-Vocabulary Image Classification

4. ImageNet Large Scale Visual Recognition Challenge

5. YFCC100M: The New Data in Multimedia Research

6. Wikipedia Bibliography:

   1. Loss function

   2. Flickr