danielshaving/RNN_for_Handwriting_Recognition

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Python
Created over 5 years ago
Updated over 5 years ago

danielshaving/RNN_for_Handwriting_Recognition

danielshaving

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Pure numpy RNN recognition for MNIST datasets

redis-cpp17

redis-cpp17 is a cross platfrom compatible redis protocol with multithreaded c++17 client,server,proxy

net-cpp17

This is a cross platfporm c++ tcp multi-threaded network library. Compared with libevent 4096kb throughput, 25-30% faster, event processing performance slightly better than libevent. Specific benchmark Please refer to the libev manual bench.c

CV_Features_HoG_Feature_Extraction

This is the HoG feature extraction codes by pure numpy

dnCNN_keras

Implementation of denoisy CNN algorithms by Keras

MNIST_handwriting_recognition_by_SKlearn_KNN

By applying KNN method from SKlearn to simply train the pixels of handwriting with supervised labels

simple_handwriting_recognition_by_KNN

Using pure numpy to make KNN classification for MNIST datasets

CVFeatures_fast_Harris_Corner_Extraction

Harris Conner key points and descriptors extraction by pure numpy

Very_Simple_Face_Detection_by_OpenCV

This is a very simple image face detection python program by using haarcascades training set of OpenCV

Keras_Fishing_Recognition

By using the test sets from Kaggle to recognize different fish pictures (InceptionV3 Network)

BlobFrameImage_googlenet_trained_caffe_model_to_do_ObjDetection

Easiest way to test the image classification(Googlenet trained)

Forehead_and_Background_Separation

Algorithm to separate the forehead and background by using Kmeans method

selenium

a selenium project

Dataguru_Tutorials

This is an on-going building model for the tutorials of object detection with my slides and codings.