Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Xnnpack | 1,641 | 3 months ago | 71 | other | C | |||||
High-efficiency floating-point neural network inference operators for mobile, server, and Web | ||||||||||
Medicaldetectiontoolkit | 1,249 | 3 months ago | 44 | apache-2.0 | Python | |||||
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images. | ||||||||||
Attn2d | 475 | 3 years ago | mit | Python | ||||||
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction | ||||||||||
Lifting From The Deep Release | 391 | 4 years ago | gpl-3.0 | Python | ||||||
Implementation of "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image" | ||||||||||
3dmmasstn | 194 | 6 years ago | 5 | apache-2.0 | Matlab | |||||
MatConvNet implementation for incorporating a 3D Morphable Model (3DMM) into a Spatial Transformer Network (STN) | ||||||||||
Image To 3d Bbox | 177 | 5 years ago | 9 | Jupyter Notebook | ||||||
Build a CNN network to predict 3D bounding box of car from 2D image. | ||||||||||
Elektronn3 | 161 | 1 | 5 months ago | 2 | June 22, 2023 | 5 | mit | Python | ||
A PyTorch-based library for working with 3D and 2D convolutional neural networks, with focus on semantic segmentation of volumetric biomedical image data | ||||||||||
Squeeze_and_excitation | 140 | 4 years ago | 3 | mit | Python | |||||
PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks | ||||||||||
Lung Segmentation 2d | 128 | 4 years ago | 1 | mit | Python | |||||
Lung fields segmentation on CXR images using convolutional neural networks. | ||||||||||
Unet | 126 | 3 | 6 months ago | 16 | December 22, 2020 | mit | Python | |||
"pip install unet": PyTorch Implementation of 1D, 2D and 3D U-Net architecture. |