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Hi there, I'm Chunyan👋!

  • 🌱 I'm currently a M.D. student at China Agricultural University. Before that, I received my Bachelor’s degree in July 2021.

  • 😎 I’m currently working on Behavior Recognition tasks, especially Object Detection and Action Recognition.

  • 📫 How to reach me: [email protected]

  • 🌸 🐰 🌸

chunyan's Projects

darknet-1 icon darknet-1

darknet深度学习框架源码分析:详细中文注释,涵盖框架原理与实现语法分析

darknet-2 icon darknet-2

Darknet(AB版)框架源码解析:详尽的中文注释(逐句)和原理分析!

darknet-3 icon darknet-3

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

detectron2 icon detectron2

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

dino icon dino

Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"

efficientdet-tf2 icon efficientdet-tf2

这是一个efficientdet-tf2(tensorflow2)的源码,可以用于训练自己的模型。

github-chinese-top-charts icon github-chinese-top-charts

:cn: GitHub中文排行榜,各语言分设「软件 | 资料」榜单,精准定位中文好项目。各取所需,高效学习。

keras-attention icon keras-attention

这个仓库主要包含了LSTM、卷积神经网络中,注意力机制的实现。

learn_python3_spider icon learn_python3_spider

python爬虫教程系列、从0到1学习python爬虫,包括浏览器抓包,手机APP抓包,如 fiddler、mitmproxy,各种爬虫涉及的模块的使用,如:requests、beautifulSoup、selenium、appium、scrapy等,以及IP代理,验证码识别,Mysql,MongoDB数据库的python使用,多线程多进程爬虫的使用,css 爬虫加密逆向破解,JS爬虫逆向,分布式爬虫,爬虫项目实战实例等

nlp-paper icon nlp-paper

自然语言处理领域下的对话语音领域,整理相关论文(附阅读笔记),复现模型以及数据处理等(代码含TensorFlow和PyTorch两版本)

pyskl icon pyskl

A toolbox for skeleton-based action recognition.

python-spider icon python-spider

:rainbow:Python3网络爬虫实战:淘宝、京东、网易云、B站、12306、抖音、笔趣阁、漫画小说下载、音乐电影下载等

pytorch-grad-cam icon pytorch-grad-cam

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

slowfast-keras icon slowfast-keras

A implementation of "SlowFast Networks for Video Recognition" with tf.keras

waking-up icon waking-up

计算机基础(计算机网络/操作系统/数据库/Git...)面试问题全面总结,包含详细的follow-up question以及答案;全部采用【问题+追问+答案】的形式,即拿即用,直击互联网大厂面试:rocket:;可用于模拟面试、面试前复习、短期内快速备战面试...

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