Zhang Guanqun's repositories

CNN-for-Face-Image-Retrieval

:apple:Face image rerieval

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caffe-face

This branch is developed for deep face recognition

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caffe-yolo

YOLO (Real-Time Object Detection) in caffe

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caffe-yolo-1

Caffe for YOLO

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caffe2

Caffe2 is a cross-platform framework made with expression, speed, and modularity in mind.

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Custom-iOS-Keyboards

Easily customizable custom inputView for iOS that imitates the native iOS keyboard.

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deep_ocr

make a better chinese character recognition OCR than tesseract

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face_verification_experiment

A Light CNN for Deep Face Representation with Noisy Labels

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facerec

Implements face recognition algorithms for MATLAB/GNU Octave and Python.

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kaldi

This is the official location of the Kaldi project.

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kaldi-offline-transcriber

Offline transcription system for Estonian using Kaldi

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KeyboardDemo

A custom iOS keyboard demo.

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LAVFilters

LAV Filters - Open-Source DirectShow Media Splitter and Decoders

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LSTM_PIT_Speech_Separation

Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.

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mtcnn-caffe

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks

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multipathnet

A Torch implementation of the object detection network from "A MultiPath Network for Object Detection" (https://arxiv.org/abs/1604.02135)

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py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

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py-R-FCN

R-FCN with joint training and python support

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R-FCN

R-FCN: Object Detection via Region-based Fully Convolutional Networks

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real_time_face_recognition

Real time face detection and recognition base on opencv/tensorflow/mtcnn/facenet

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RobustVideoMatting

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

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Spoken_language_identification

A TensorFlow-based spoken language identification

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vue-upload-component

Vue.js file upload component, Multi-file upload, Upload directory, Drag upload, Drag the directory, Upload multiple files at the same time, html4 (IE 9), `PUT` method, Customize the filter

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