A simple and flexible code for Reservoir Computing architectures like Echo State Networks

Awesome tutorials, papers, projects and tools for Reservoir Computing techniques like Echo State Networks (ESN).

3D点云语义分割汇总，所有顶会论文以及一些arxiv上的最新论文

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

LeetCode 刷题攻略：配思维导图，100+经典算法题目刷题顺序、经典算法模板、共40w字的详细图解，以及难点视频题解。按照刷题攻略上的顺序来刷题，让你在算法学习上不再迷茫！🔥🔥给个star支持一下吧！🚀

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

A collection of loss functions for medical image segmentation

stock，股票系统。使用python进行开发。

LeetCode刷题记录与面试整理

YOLO ModelCompression MultidatasetTraining

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

Automatic License Plate Recognition library

some algorithm about self-driving car，mainly including perception algorithm，2D/3D object detection，Semantic segmentation and so on

Critical difference diagram with Wilcoxon-Holm post-hoc analysis.

Google Brain AutoML

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

ROS communications-related packages, including core client libraries (roscpp, rospy, roslisp) and graph introspection tools (rostopic, rosnode, rosservice, rosparam).

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

AI系统化学习路径

🤘 awesome-semantic-segmentation

TensorFlow Tutorials with YouTube Videos

B站Efficient-Neural-Network学习分享的配套代码

High-level library to help with training neural networks in PyTorch

A simplified implemention of Faster R-CNN that replicate performance from origin paper

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

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