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arucoronghe

使用aruco进行图像融合

biubiu0719.github.io

caffe

Caffe: a fast open framework for deep learning.

csrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

darknet

YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )

darknet2caffe

Convert darknet weights to caffemodel

efficientnet-pytorch

A PyTorch implementation of EfficientNet

fisco_project

区块链项目

hello_github

入门

hog_svm

利用Hog特征使用svm进行二分类

idea-test

IDEA后端模板

kmeans-anchor-boxes

k-means clustering with the Intersection over Union (IoU) metric as described in the YOLO9000 paper

lbp_svm

使用lbp特征使用svm进行二分类

merge_bn_caffe

Merge Batch Norm caffe

mobilenet-yolo

MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:

mobilenetv2

A Keras implementation of MobileNetV2.

mobilenetv2.pytorch

72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models

mobilenetv3

mobilenetv3 with pytorch，provide pre-train model

os_lab

简易操作系统实验

pelee

Pelee: A Real-Time Object Detection System on Mobile Devices

pytorch-cifar

95.16% on CIFAR10 with PyTorch

pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

shufflenetv2_pytorch2caffe

shufflenetv2使用pytorch训练2分类模型，转换为caffe，可压缩模型简化网络

sysu_computer-network

SYSU_Computer-network

vue-test

vue前端模板

yolo-fastest

:zap: Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB

yolov5

YOLOv5 in PyTorch > ONNX > CoreML > iOS

yolov5_ncnn

🍅 Ncnn deployment on mobile,support:YOLOv5s,YOLOv4-tiny,MobileNetV2-YOLOv3-nano,Simple-Pose,Yolact,ChineseOCR-lite,ENet,Landmark106,DBFace,MBNv2-FCN and MBNv3-Seg-small on camera.