gradientdescentex,GradientDiscentEX,github

autokeras

Accessible AutoML for deep learning.

awesome-lane-detection

A paper list of lane detection.

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

bgslibrary

A Background Subtraction Library

chineseocr

yolo3+ocr

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_20210304

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

deep-learning-models

Keras code and weights files for popular deep learning models.

deep-learning-with-pytorch-tutorials

深度学习与PyTorch入门实战视频教程

easypr

An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations.

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

gluon-cv

Gluon CV Toolkit

hyperlpr

基于深度学习高性能中文车牌识别 High Performance Chinese License Plate Recognition Framework.

jionlp

中文 NLP 预处理、解析工具包，准确、高效、易用 A Chinese NLP Preprocessing & Parsing Package

keras-applications

Reference implementations of popular deep learning models.

keras-fcn

Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation（Unfinished）

keras-retinanet

Keras implementation of RetinaNet object detection.

keras-vgg16-places365

Keras code and weights files for the VGG16-places365 and VGG16-hybrid1365 CNNs for scene classification

keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)

kittiseg

A Kitti Road Segmentation model implemented in tensorflow.

lanenet-lane-detection

Implemention of lanenet model for real time lane detection using deep neural network model https://maybeshewill-cv.github.io/lanenet-lane-detection/

lihang-code

《统计学习方法》的代码实现

lihang_book_algorithm

致力于将李航博士《统计学习方法》一书中所有算法实现一遍

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

models

Models and examples built with TensorFlow

models-1

Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）

mosse-object-tracking

This is the implementation of MOSSE tracking algorithm (correlation filter based).

multinet

Real-time Joint Semantic Reasoning for Autonomous Driving

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