Pinned Repositories
30-Days-of-ML-Kaggle
Machine learning beginner to Kaggle competitor in 30 days. Non-coders welcome. The program starts Monday, August 2, and lasts four weeks. It's designed for people who want to learn machine learning.
arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
d2l-zh-pytorch-slides
Pytorch版代码幻灯片
deeplearning-architectures
DeepLearning-MuLi-Notes
Notes about courses Dive into Deep Learning by Mu Li
DensePoint
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing (ICCV 2019)
EEG-based-emotion-analysis-using-DEAP-dataset-for-Supervised-Machine-Learning
This project is for classification of emotions using EEG signals recorded in the DEAP dataset to achieve high accuracy score using machine learning algorithms such as Support vector machine and K - Nearest Neighbor.
EEG-DCGAN
To generate artificial EEG data
pytorch_classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
SENet-PyTorch
Rongzhq's Repositories
Rongzhq/pytorch_classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
Rongzhq/30-Days-of-ML-Kaggle
Machine learning beginner to Kaggle competitor in 30 days. Non-coders welcome. The program starts Monday, August 2, and lasts four weeks. It's designed for people who want to learn machine learning.
Rongzhq/arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
Rongzhq/d2l-zh-pytorch-slides
Pytorch版代码幻灯片
Rongzhq/deeplearning-architectures
Rongzhq/DeepLearning-MuLi-Notes
Notes about courses Dive into Deep Learning by Mu Li
Rongzhq/DensePoint
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing (ICCV 2019)
Rongzhq/EEG-based-emotion-analysis-using-DEAP-dataset-for-Supervised-Machine-Learning
This project is for classification of emotions using EEG signals recorded in the DEAP dataset to achieve high accuracy score using machine learning algorithms such as Support vector machine and K - Nearest Neighbor.
Rongzhq/EEG-DCGAN
To generate artificial EEG data
Rongzhq/EEG-Emotion-classification
Rongzhq/EEG_classification
Implementing different deep learning architecture using pyTorch to classify EEG signals.
Rongzhq/EEG_GAN-master
Rongzhq/facemesh.pytorch
This is the PyTorch implementation of paper Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs (https://arxiv.org/pdf/1907.06724.pdf)
Rongzhq/Facial-Expression-Recognition
Facial expression classification using salient pattern driven integrated geometric and textual features
Rongzhq/Facial_106_Landmarks
Facial_106_Landmarks
Rongzhq/Graph-CNN-in-3D-Point-Cloud-Classification
Code for A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION (ICASSP 2018)
Rongzhq/ltp
Language Technology Platform
Rongzhq/merge-ply
合并多个点云.ply文件
Rongzhq/model-converter-python
Mirror of model-converter-python
Rongzhq/Obj2ply
Complete conversion of object files to ply files with color encdoing as well as uv coordiantes.
Rongzhq/paper-reading-limu
深度学习经典、新论文逐段精读
Rongzhq/pfld_106_face_landmarks
106点人脸关键点检测的PFLD算法实现
Rongzhq/Pointnet_Pointnet2_pytorch
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Rongzhq/pytorch_geometric
Graph Neural Network Library for PyTorch
Rongzhq/pytorch_image_classification
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST
Rongzhq/segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
Rongzhq/Seizure-Detection-using-CNN-on-EEG-data
Electroencephalogram(EEG) benchmark dataset Chb-mit is used for seizure detection.
Rongzhq/test-
项目描述
Rongzhq/TheAlgorithms-Python
TheAlgorithms/Python
Rongzhq/torch-points3d
Pytorch framework for doing deep learning on point clouds.