github repo
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- 一个SSD算法的实现
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jbhuang0604/awesome-computer-vision
- A curated list of awesome computer vision resources
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AgaMiko/data-augmentation-review
- List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.
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aleju/imgaug
- Image augmentation for machine learning experiments.
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Paperspace/DataAugmentationForObjectDetection
- Data Augmentation For Object Detection
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Paperspace/DataAugmentationForObjectDetection
- https://github.com/amusi
- Image augmentation for machine learning experiments.
- Mnist数据集链接可以用这里
- 替代已经失效的lecun网址
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ysh329/deep-learning-model-convertor
- The convertor/conversion of deep learning models for different deep learning frameworks/softwares.
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Mathematics for Machine Learning
- We wrote a book on Mathematics for Machine Learning that motivates people to learn mathematical concepts. The book is not intended to cover advanced machine learning techniques because there are already plenty of books doing this. Instead, we aim to provide the necessary mathematical skills to read those other books.
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FLHonker/ZAQ-code
- CVPR 2021 : Zero-shot Adversarial Quantization (ZAQ),包含一些量化的自主实现,可参考理解原理。
- Openpose作者本者开的Openpose repo
- 相比于CMU-Lab的这个相比更偏Python
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jbhuang0604/awesome-tips
- A curated list of tips on various topics.
Website
- stanford CS231n Convolutional Neural Networks for Visual Recognition
- ConvNetJS - Deep Learning in your browser
- Web入门
- 英伟达显卡计算能力(Compute Capability)查询与支持的运算类型查询
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CVonline: Image Databases
- a collated list of image and video databases that people have found useful for computer vision research and algorithm evaluation.
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如何解决神经网络训练时loss不下降的问题
- 当出现loss不下降时,可以对照一下
- The Missing Semester of Your CS Education
知乎
视频
3Blue1Brown series 反向传播演算(第 3 季 • 第 4 集)
Blog
- Graph Convolutional Networks (GCN) & Pooling
- Object Detection Paper collection
- Self-Supervised Representation Learning
- 台湾清华彭明辉教授的研究生手册(简体完全版)
- A Beginner’s Guide To Understanding Convolutional Neural Networks(这个博主写的文章挺不错的)
- 一文搞懂交叉熵在机器学习中的使用,透彻理解交叉熵背后的直觉
- The Illustrated Transformer
- Do We Really Need Model Compression?
- Object Detection Series of Lil’Log: part1 part2 part3 part4
- 为什么你应该(从现在开始就)写博客
- debug DNN model
- 一篇历时五年的心得体会:关于AI部署、关于选择方向、关于就业
TEDs
Projects
- mediapipe:这也太牛了吧!
环境配置
- Windows下C++编译器下载与配置:MinGW C++ Download and Installation
- 基于Chrome获取Andriod端浏览器log:How to get the web console log in Chrome for Android