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GoogLeNet

2000년 도입 · 논문 122편에서 사용

GoogLeNet is a type of convolutional neural network based on the Inception architecture. It utilises Inception modules, which allow the network to choose between multiple convolutional filter sizes in each block. An Inception network stacks these modules on top of each other, with occasional max-pooling layers with stride 2 to halve the resolution of the grid.

출처: Going Deeper with Convolutions

소개 논문: Going Deeper with Convolutions

Convolutional Neural Networks · Computer Vision