ML Paper Challenge Day 36, 37— Building high-level features using large scale unsupervised learning

Papers with Code - Building high-level features using large scale unsupervised learning

Day 36–37: 2020.05.17–18
Paper: Building high-level features using large scale unsupervised learning
Category: Model/Unsupervised Learning

This paper is a milestone. The main topic there is to prove that it is possible to learn some high-level features without any labelled data.

Result First:

• A neuron is learnt to classify face image with 81.7% accuracy.
• A neuron is learnt to classify cat and human body image with 74.8% and 76.7% respectively.
• Control experiments show that the learned detector is not only invariant to translation but also to out-of-plane rotation and scaling.