recapture2018 Goto Github PK

2020vrpso

RLPSO->VRPSO

2e-vrp-abc

In the process of solving the 2E-VRP problem, the large-scale destruction and repair algorithm is used to ensure that the algorithm does not fall into the local optimal solution. The process of the initialization process uses the greedy strategy to cluster the customers. The large-scale destruction process is to randomly remove the customer nodes on the satellite into the customer pool. The repair process is based on the reciprocal of the customer's distance to each customer in the customer pool. Gambling Select the satellite to which the customer belongs and engage in greedy insertion. For the second layer of path planning, you need to use multiple search operators, such as random sequence reversal exchange operator, crossover operator, damage and repair operator, and crossover operator variants, etc. to improve the artificial bee group algorithm Of the local search ability. To ensure that the global optimal situation can be found, the neighborhood of large-scale search. The improved artificial bee colony algorithm incorporates the idea of ​​simulated annealing and improves the global optimization ability of artificial bee colony algorithm. For the artificial bee colony algorithm, the combination of global optimization ability and local optimization ability improves the possibility that the algorithm can find a better solution than the existing method. Multi - operator artificial bee colony algorithm, which extends the search range of the food source 's neighborhood, and more possibilities to find the global optimal solution. The experimental results show that the algorithm can get better path planning results

aibook

Ai book

api-demo

awesome-meta-learning

A curated list of Meta-Learning resources/papers.

bisenet

Add bisenetv2. My implementation of BiSeNet backbone with resnet18

chatgpt-on-wechat

基于大模型搭建的聊天机器人，同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入，可选择GPT3.5/GPT-4o/GPT4.0/ Claude/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Claude/Kimi/LinkAI，能处理文本、语音和图片，访问操作系统和互联网，支持基于自有知识库进行定制企业智能客服。

coverage_path_planning-

This project aims at generating an optimal coverage planning algorithm based on linear sweep based decomposition - the algorithm uses pseudo-spectral optimal control to generate time-energy optimal trajectories for a given area in presence of obstacles.

cv-clas_with_-pytorch

cvpr2023-paper-code-interpretation

cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。

d_star_pathplanning

Simple Matlab implementation of D*Lite, Focussed D*, A*, for dynamic path planning for mobile robots

deep-learning-with-pytorch-tutorials

深度学习与PyTorch入门实战视频教程 配套源代码和PPT

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

deepreinforcementlearning-quadrupedrobottrainingtutorial

digital-image-processing

冈萨雷斯《数字图像处理matlab版》第二版

dimensionality_reduction_alo_codes

特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现

dive-into-dl-tensorflow2.0

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的同意

djangoblog

🍺基于Django的博客系统

dynamic_unet

Pytorch Implementation of UNET with Efficientnet(Efficient Unet), Resnet, Densenet, VGG and so on.

ecg-ml-dl-algorithm-matlab

Basic Algorithm For Beginners

ecg-ml-dl-algorithm-python

Basic Algorithm For Beginners （Python version）

eldo_afsa-clone-

this is copy version of my private project ELDO_AFSA

faster-rcnn-tensorflow-with-dense

DenseNet with Faster R-CNN by tf for Windows/Linux

faster_rcnn

Faster R-CNN

flash-reflection-removal

Code for CVPR2021 paper "Robust Reflection Removal with Reflection-free Flash-only Cues"

formation_flight_sim

The simulation of formation control for quadrotor, including target allocation, global path planning and local path planning

indoor_navigation

A indoor navigation program which takes floor plan image as input and corresponding XML file. And generate the appropriate path from a source door to all the doors that are present in that floor.

learningtocompare-pytorch

Pytorch Implementation for CVPR2018 Paper: Learning to Compare: Relation Network for Few-Shot Learning

lightcapsnet

A Matlab implementation of the capsule networks (or capsnet).