Pinned Repositories
CarPlateIdentity
车牌识别
Charging_demand_simulation_STEP-TV
A spatial-temporal simulation model for EV charging demand
Clustering-Algorithms
基于Python实现了K-Means、GMM、DBSCAN、AGNES等四种常见的聚类算法
data_mine
Apriori and fp-growth implement of python
em
em算法python实现
End-to-end-for-chinese-plate-recognition
基于u-net，cv2以及cnn的中文车牌定位，矫正和端到端识别软件，其中unet和cv2用于车牌定位和矫正，cnn进行车牌识别，unet和cnn都是基于tensorflow的keras实现
fengchen1999.github.io
gmm
Gaussian Mixture Models in Python
google-research
Google Research
machine_learning_python
通过阅读网上的资料代码，进行自我加工，努力实现常用的机器学习算法。实现算法有KNN、Kmeans、EM、Perceptron、决策树、逻辑回归、svm、adaboost、朴素贝叶斯
fengchen1999's Repositories
fengchen1999/Charging_demand_simulation_STEP-TV
A spatial-temporal simulation model for EV charging demand
fengchen1999/CarPlateIdentity
车牌识别
fengchen1999/Clustering-Algorithms
基于Python实现了K-Means、GMM、DBSCAN、AGNES等四种常见的聚类算法
fengchen1999/data_mine
Apriori and fp-growth implement of python
fengchen1999/em
em算法python实现
fengchen1999/End-to-end-for-chinese-plate-recognition
基于u-net，cv2以及cnn的中文车牌定位，矫正和端到端识别软件，其中unet和cv2用于车牌定位和矫正，cnn进行车牌识别，unet和cnn都是基于tensorflow的keras实现
fengchen1999/fengchen1999.github.io
fengchen1999/gmm
Gaussian Mixture Models in Python
fengchen1999/google-research
Google Research
fengchen1999/machine_learning_python
通过阅读网上的资料代码，进行自我加工，努力实现常用的机器学习算法。实现算法有KNN、Kmeans、EM、Perceptron、决策树、逻辑回归、svm、adaboost、朴素贝叶斯
fengchen1999/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
fengchen1999/TransportationNetworks
Transportation Networks for Research