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 sizePaper | Code | Results | Date | Stars |
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Task | Papers | Share |
---|---|---|
General Classification | 11 | 10.58% |
Object Detection | 10 | 9.62% |
Classification | 8 | 7.69% |
Image Classification | 7 | 6.73% |
Quantization | 4 | 3.85% |
Face Recognition | 3 | 2.88% |
Face Verification | 3 | 2.88% |
Specificity | 3 | 2.88% |
Object Recognition | 3 | 2.88% |