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yhl41001's Projects

adaboost icon adaboost

A simple C++ implementation of the AdaBoost algorithm

bolt icon bolt

Bolt is a deep learning library with high performance and heterogeneous flexibility.

centermulti icon centermulti

基于CenterNet训练的目标检测&人脸对齐&姿态估计模型

centernet_pro_max icon centernet_pro_max

Experiments based on CenterNet (more backbones, TensorRT deployment and mask head)

chineseocr_lite icon chineseocr_lite

超轻量级中文ocr,支持竖排文字识别, 支持ncnn推理 , psenet(8.5M) + crnn(6.3M) + anglenet(1.5M) 总模型仅17M

d2l-zh icon d2l-zh

《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被全球175所大学采用教学。

darknet icon darknet

Windows and Linux version of Darknet Yolo v4 (v3/v2) Neural Networks for object detection (Tensor Cores are used)

deeplearning icon deeplearning

Python for “Deep Learning”,《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

deeplearning-500-questions icon 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[email protected] 版权所有,违权必究 Tan 2018.06

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet代码实现改为PyTorch实现。

dmfn icon dmfn

unofficial implement of DMFN

ebook icon ebook

classic books of computer science!

fucking-algorithm icon fucking-algorithm

手把手撕LeetCode题目,扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.

hccr-googlenet icon hccr-googlenet

This project is about directional feature extraction and HCCR-GoogLeNet CNN architecture definition for Caffe platform.

hmfaysal-omega-theme icon hmfaysal-omega-theme

HMFAYSAL OMEGA is a minimalist, beautiful, responsive theme for Jekyll designed for writers who want their content to take front and center.

imgaug icon imgaug

Image augmentation for machine learning experiments.

interpretablemlbook icon interpretablemlbook

《可解释的机器学习--黑盒模型可解释性理解指南》,该书为《Interpretable Machine Learning》中文版

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

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