ss_Jia's repositories
Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
amemv-crawler
🙌Easily download all the videos from TikTok(amemv).下载指定的 抖音（Douyin） 号的视频,抖音爬虫
astro-stacker
A simple python3 application to stack and optionally align raw images to reduce noise
awesome-computer-vision
A curated list of awesome computer vision resources
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
BaiduImageSpider
一个超级轻量的百度图片爬虫
deeplearning_ai_books
deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）
Deformable-Convolution-V2-PyTorch
Deformable ConvNets V2 (DCNv2) in PyTorch
EfficientNet-PyTorch
A PyTorch implementation of EfficientNet
hiddenlayer
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
HRNet-Semantic-Segmentation
This is an official implementation of semantic segmentation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
leeml-notes
李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes
lihang-code
《统计学习方法》的代码实现
maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
mmdetection
Open MMLab Detection Toolbox and Benchmark
py-MDNet
MDNet PyTorch implementation
pytorch-beginner
pytorch tutorial for beginners
pytorch-cifar
95.16% on CIFAR10 with PyTorch
pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
PyTorch-Networks
Pytorch implementation of cnn network
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
PyTorch_Tutorial
《Pytorch模型训练实用教程》中配套代码
ScaledYOLOv4
:fire::fire::fire: Scaled-YOLOv4训练自己的数据集详细教程PDF，关于paper解读请联系小编获取PDF文档
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Tianchi-2019-Guangdong-Intelligent-identification-of-cloth-defects-rank5
天池2019广东工业智造创新大赛 布匹疵点检测 天池水也太深了 季军解决方案
xml2json-txt2xml-csv2txt
Some common data processing scripts
Yet-Another-EfficientDet-Pytorch
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.