Image Model Blocks

Inception Module

Introduced by Szegedy et al. in Going Deeper with Convolutions

An Inception Module is an image model block that aims to approximate an optimal local sparse structure in a CNN. Put simply, it allows for us to use multiple types of filter size, instead of being restricted to a single filter size, in a single image block, which we then concatenate and pass onto the next layer.

Source: Going Deeper with Convolutions

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
General Classification 30 13.70%
Image Classification 29 13.24%
Object Detection 18 8.22%
Computer Vision 12 5.48%
Quantization 11 5.02%
Object Recognition 8 3.65%
Autonomous Driving 5 2.28%
Domain Adaptation 5 2.28%
Image Generation 3 1.37%

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