Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Enzynet | 188 | 9 months ago | 9 | mit | Python | |||||
EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation | ||||||||||
Dynconv | 103 | 2 years ago | 9 | Cuda | ||||||
Code for Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference (CVPR2020) | ||||||||||
Mnist1d | 76 | a year ago | apache-2.0 | Jupyter Notebook | ||||||
A 1D analogue of the MNIST dataset for measuring spatial biases and answering "science of deep learning" questions. | ||||||||||
Stn_idsia_convnet | 54 | 7 years ago | 4 | Jupyter Notebook | ||||||
An implementation of a convolutional neural network with a spatial transformer | ||||||||||
Embedded_gcnn | 54 | 6 years ago | 5 | mit | Jupyter Notebook | |||||
Embedded Graph Convolutional Neural Networks (EGCNN) in TensorFlow | ||||||||||
Fbcnet | 43 | a year ago | 2 | mit | Python | |||||
FBCNet: An Efficient Multi-view Convolutional Neural Network for Brain-Computer Interface | ||||||||||
Hyperspectral Image Spatial Super Resolution Via 3d Full Convolutional Neural Network | 36 | 6 years ago | 4 | bsd-3-clause | Python | |||||
Hyperspectral Image Spatial Super-Resolution via 3D-Full-Convolutional-Neural-Network | ||||||||||
Gcnn | 33 | 3 years ago | 1 | Python | ||||||
A graph convolutional neural network for classification of building patterns using spatial vector data | ||||||||||
Snn Iir | 32 | 3 years ago | 1 | Python | ||||||
This repo contains the implementation of paper Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network. It trains spiking neural network to learn spatial temporal patterns. | ||||||||||
Sensor Specific Hyperspectral Image Feature Learning | 31 | 7 years ago | 1 | apache-2.0 | Python | |||||
Learning Sensor-Specific Spatial-Spectral Features of Hyperspectral Images via Convolutional Neural Networks |