Miscellaneous Components

Auxiliary Classifier

Auxiliary Classifiers are type of architectural component that seek to improve the convergence of very deep networks. They are classifier heads we attach to layers before the end of the network. The motivation is to push useful gradients to the lower layers to make them immediately useful and improve the convergence during training by combatting the vanishing gradient problem. They are notably used in the Inception family of convolutional neural networks.

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
General Classification 47 13.17%
Image Classification 41 11.48%
Semantic Segmentation 26 7.28%
Object Detection 19 5.32%
Quantization 15 4.20%
Image Generation 9 2.52%
Autonomous Driving 9 2.52%
Object Recognition 9 2.52%
Scene Parsing 7 1.96%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories