CondenseNet
CNN architechture
An efficient CNN architecture for mobile devices with learned group convolutions and dense connectivity
CondenseNet: Light weighted CNN for mobile devices
694 stars
24 watching
131 forks
Language: Python
last commit: about 5 years ago
Linked from 2 awesome lists
deep-learningmobile-devicepytorch
Related projects:
Repository | Description | Stars |
---|---|---|
mg2033/shufflenet | An implementation of a computationally efficient deep neural network architecture designed for mobile devices with limited computing power. | 384 |
benedekrozemberczki/mixhop-and-n-gcn | A deep learning framework implementation of higher-order graph convolutional architectures and their applications | 402 |
xuzhenqi/cnn | Provides an implementation of convolutional neural networks in MATLAB. | 95 |
ahmedfgad/numpycnn | Builds convolutional neural networks from scratch using NumPy | 572 |
jihongju/keras-fcn | A library implementing a Fully Convolutional Network architecture with Keras support | 202 |
benedekrozemberczki/sgcn | An implementation of a deep learning algorithm for graph data | 268 |
charlotte-pel/temporalcnn | A deep learning-based approach to classifying satellite image time series using convolutional neural networks. | 149 |
wkentaro/fcn | An implementation of fully convolutional networks in Chainer, a deep learning framework. | 218 |
markdtw/condensenet-tensorflow | An implementation of CondenseNet, a model for efficient neural networks using learned group convolutions. | 29 |
implus/sknet | Implementation of a deep learning model that combines convolutional neural networks with selective kernel networks for image recognition tasks. | 593 |
preritj/segmentation | Deep learning models for semantic segmentation of images | 100 |
shicai/densenet-caffe | Provides pre-trained neural network models based on DenseNet architecture, converted from Torch format to Caffe model for use in deep learning applications. | 357 |
pistony/residualattentionnetwork | A Gluon implementation of Residual Attention Network for image classification tasks | 107 |
jhkim89/pyramidnet | A Torch implementation of a novel neural network architecture designed to improve the generalization ability of deep image classification models. | 129 |
terrychenism/deformable-convnets | An implementation of deformable convolutional networks for object detection and segmentation tasks | 160 |