gqcnn
Grasp Quality CNN
Develops and analyzes convolutional neural networks for grasp quality in robotics
Python module for GQ-CNN training and deployment with ROS integration.
313 stars
32 watching
149 forks
Language: Python
last commit: 7 months ago
Linked from 1 awesome list
deep-learninggqcnngraspingmachine-learningpythonroboticsros
ahundt/awesome-roboticsRelated projects:
| Repository | Description | Stars |
|---|---|---|
 dougsm/ggcnn | A deep learning-based system for generating precise grasp poses for robots in real-time | 514 |
 nv-tlabs/gscnn | This code implements a neural network architecture designed to perform semantic segmentation in computer vision tasks. | 920 |
 ahmedfgad/cnngenetic | Trains CNNs using the genetic algorithm | 22 |
 wkentaro/fcn | An implementation of fully convolutional networks in Chainer, a deep learning framework. | 218 |
| ahmedfgad/numpycnn | Builds convolutional neural networks from scratch using NumPy | 572 |
 benedekrozemberczki/mixhop-and-n-gcn | A deep learning framework implementation of higher-order graph convolutional architectures and their applications | 402 |
 liqimai/gcn | An implementation of graph convolutional networks for semi-supervised learning in Python using TensorFlow and other libraries. | 45 |
 pistony/residualattentionnetwork | A Gluon implementation of Residual Attention Network for image classification tasks | 107 |
 bowenbaker/metaqnn | Automatically designs convolutional neural network architectures using reinforcement learning and Q-learning algorithms | 137 |
 hagaygarty/mdcnn | A 3D convolutional neural network framework supporting volumetric inputs and various features like dropout and batch normalization. | 52 |
 cszn/ircnn | This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. | 600 |
 aqibsaeed/genetic-cnn | A tool for exploring and optimizing the architecture of Convolutional Neural Networks using a Genetic Algorithm | 218 |
 matenure/fastgcn | Implementation of graph convolutional network algorithms with sampling techniques to improve learning speed and efficiency | 519 |
 google-research/big_transfer | Pre-trained models and code for fine-tuning image recognition tasks using deep learning frameworks | 1,513 |
| ahmedfgad/neuralgenetic | Trains artificial neural networks using the genetic algorithm to optimize regression or classification tasks | 241 |