Densely Connected Convolutional Networks

GPTKB entity

Predicate	Object
gptkbp:instanceOf	deep learning architecture
gptkbp:abbreviation	gptkb:DenseNet
gptkbp:application	image classification object detection semantic segmentation
gptkbp:architecture	gptkb:feedforward_neural_network
gptkbp:arXivID	arXiv:1608.06993
gptkbp:bench	gptkb:SVHN gptkb:CIFAR-10 gptkb:CIFAR-100 gptkb:ImageNet
gptkbp:citation	highly cited
gptkbp:contribution	reduces number of parameters alleviates vanishing-gradient problem improves information flow and gradient propagation introduces dense connectivity between layers
gptkbp:features	feature reuse improved parameter efficiency compact model size each layer receives input from all previous layers
https://www.w3.org/2000/01/rdf-schema#label	Densely Connected Convolutional Networks
gptkbp:improves	ResNet on several benchmarks
gptkbp:influenced	subsequent neural network architectures
gptkbp:notablePublication	gptkb:Densely_Connected_Convolutional_Networks
gptkbp:openSource	gptkb:TensorFlow gptkb:Keras gptkb:PyTorch
gptkbp:proposedBy	gptkb:Laurens_van_der_Maaten gptkb:Gao_Huang gptkb:Kilian_Q._Weinberger gptkb:Zhuang_Liu
gptkbp:publicationYear	2017
gptkbp:publishedIn	gptkb:CVPR_2017
gptkbp:relatedTo	gptkb:ResNet Convolutional Neural Networks
gptkbp:uses	batch normalization convolutional layers bottleneck layers ReLU activation transition layers
gptkbp:bfsParent	gptkb:DenseNet
gptkbp:bfsLayer	6