xiezheng-cs

xiezheng-cs

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Company:SCUT-SMIL

Location:ShenZhen, China

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xiezheng-cs's starred repositories

mtcnn_ncnn

基于ncnn框架搭建win及android端的MTCNN人脸检测工程

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MTCNN

MTCNN face detection implementation base on NCNN

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MVision

机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶

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convNet.pytorch

ConvNet training using pytorch

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Accurate-Binary-Convolution-Network

Binary Convolution Network for faster real-time processing in ASICs

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ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

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quantized_distillation

Implements quantized distillation. Code for our paper "Model compression via distillation and quantization"

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gluon-cv

Gluon CV Toolkit

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libfacedetection

An open source library for face detection in images. The face detection speed can reach 1000FPS.

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deepfloat

An exploration of log domain "alternative floating point" for hardware ML/AI accelerators.

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facenet

Face recognition using Tensorflow

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sphereface-plus

SphereFace+ Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.

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IMDb-Face

A new large-scale noise-controlled face recognition dataset.

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caffe-int8-convert-tools

Generate a quantization parameter file for ncnn framework int8 inference

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mobileFacenet-ncnn

implementation of ncnn's mobileFacenet

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mobilefacenet-V2

🔥improve the accuracy of mobilefacenet(insight face) reached 99.733 in the cfp-ff、 the 99.68+ in lfw,96.71+ in agedb30.🔥

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models

A repository for storing pre-trained Caffe2 models.

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PocketFlow

An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.

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ncnn-mobile

use ncnn in Android and iOS, ncnn is a high-performance neural network inference framework optimized for the mobile platform

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ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

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mtcnn-pytorch

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

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mobilefacenet-mxnet

基于insightface训练mobilefacenet的相关步骤及ncnn转换流程

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DCP

Code for “Discrimination-aware-Channel-Pruning-for-Deep-Neural-Networks”

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hwgq

Caffe implementation of accurate low-precision neural networks

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DeepLearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06

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faster_rcnn_pytorch

Faster RCNN with PyTorch

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QNNPACK

Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators

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