Convolutional Neural Networks

SqueezeNet is a convolutional neural network that employs design strategies to reduce the number of parameters, notably with the use of fire modules that "squeeze" parameters using 1x1 convolutions.

Source: SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
General Classification 11 8.73%
Object Detection 10 7.94%
Image Classification 8 6.35%
Classification 8 6.35%
Deep Learning 5 3.97%
Face Recognition 4 3.17%
Quantization 4 3.17%
Object 4 3.17%
Network Pruning 3 2.38%

Categories