ML Paper Challenge Day 8— Going deeper with convolutions

Papers with Code - Going Deeper with Convolutions

Day 8: 2020.04.19
Paper: Going deeper with convolutions
Category: Model/CNN/Deep Learning/Image Recognition

This paper introduces a new concept called “Inception”, which is able to improve utilisation of computation resources inside the network. This allows increasing the depth and width while keeping the computational budget constant.

• based on the Hebbian principle & intuition of multi-scale processing
• useful in the context of localisation and object detection

Related Work:

• Series of fixed Gabor filters of different sizes: handle multiple scales
  -> In “Inception”, all filters are learned
• Network-in-Network: increase the representational power of neural networks
  additional 1 × 1 convolutional layers are added to the network
  -> In “Inception”, used mainly as dimension reduction modules to remove computational…