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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.

kcfpy

Python implementation of KCF tracking algorithm

kitti-dataset

Examination of the KITTI dataset.

laser_tape_reverse_engineering

Alternative firmware for a cheap X-40 laser tape measure

learn_github

learn to use github to mange my program

lee-slam-source

SLAM 开发学习资源与经验分享

leetcode

LeetCode Problems' Solutions

lego

LEGO: Learning Edge with Geometry all at Once by Watching Videos

libopendrive

Small, lightweight C++ library for handling OpenDRIVE files

lstr

This is an official repository of End-to-end Lane Shape Prediction with Transformers.

machine-learning

my code for machine learning

map

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

mask-rcnn

Implementation of Mask-RCNN in Caffe https://arxiv.org/pdf/1703.06870.pdf

mbmd

mmdetection

Open MMLab Detection Toolbox and Benchmark

modeld

Self driving car lane and path detection

models

Models and examples built with TensorFlow

mono_velocity

A PyTorch implementation of the ICRA 2020 paper 'End-to-end Learning for Inter-Vehicle Distance and Relative Velocity Estimation in ADAS with a Monocular Camera'.

monodepth

Unsupervised single image depth prediction with CNNs

monodepth2

Monocular depth estimation from a single image

motion-planning-and-decision-making-for-autonomous-vehicles

Implemented two of the main components of a traditional hierarchical planner: the behavior planner and the motion planner. Both work in unison to be able to avoid static objects parked on the side of the road, avoid crashing with these vehicles by executing either a “nudge” or a “lane change” maneuver, handle any type of intersection, and track the centerline on the traveling lane.

motion-planning-on-carla

Implement Motion Planning for autonomous car on CARLA simulator

motionplanning

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

my_dorn

copy the code from dorn and train the depth

myslam

fork from gaoxing

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

nim

Normal Inference Module in PyTorch, IROS 2020

normface

NormFace: L2 HyperSphere Embedding for Face Verification, 99.21% on LFW

notes-of-mpc-in-self-driving-car

读书笔记《无人驾驶车辆模型预测控制》- 龚建伟

open-adas

An open source advanced driver assistance system (ADAS) that uses Jetson Nano as the hardware. Features: Traffic sign detection, Forward collision warning, Lane departure warning.