A DenseNet is a type of convolutional neural network that utilises dense connections between layers, through Dense Blocks, where we connect all layers (with matching feature-map sizes) directly with each other. To preserve the feed-forward nature, each layer obtains additional inputs from all preceding layers and passes on its own feature-maps to all subsequent layers.
Source: Densely Connected Convolutional NetworksPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Image Classification | 59 | 13.88% |
General Classification | 58 | 13.65% |
Semantic Segmentation | 17 | 4.00% |
Object Detection | 14 | 3.29% |
Quantization | 7 | 1.65% |
Computed Tomography (CT) | 6 | 1.41% |
Out-of-Distribution Detection | 5 | 1.18% |
Domain Adaptation | 5 | 1.18% |
reinforcement-learning | 4 | 0.94% |