Scott Lee's repositories
6-DOF-Inertial-Odometry
IMU-Based 6-DOF Odometry
awesome-lane-detection
A paper list of lane detection.
Awesome-LiDAR-Camera-Calibration
A Collection of LiDAR-Camera-Calibration Papers, Toolboxes and Notes
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Dive-into-DL-PyTorch
Dive into Deep Learning (动手学深度学习) with PyTorch.
DS
cpp deep_sort: C++ implementation of Simple Online Realtime Tracking with a Deep Association Metric
ECCV2022-Papers-with-Code
ECCV 2022 论文开源项目合集，同时欢迎各位大佬提交issue，分享ECCV 2020开源项目
Entropy-and-securities-investment
Evaluate stocks using the entropy weight method and predict stocks using a decision tree algorithm
feature-selector
Feature selector is a tool for dimensionality reduction of machine learning datasets
geonav_transform
Simple transforms for using GPS-based estimates for local odometry in ROS
gnssins
Work on a tightly coupled multi-gnss integration (not complete)
GPS_IMU_Kalman_Filter
Fusing GPS, IMU and Encoder sensors for accurate state estimation.
IMU-GNSS-Lidar-sensor-fusion-using-Extended-Kalman-Filter-for-State-Estimation
State Estimation and Localization of an autonomous vehicle based on IMU (high rate), GNSS (GPS) and Lidar data with sensor fusion techniques using the Extended Kalman Filter (EKF).
Lane-Marking-Detection
This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.
measure
data measure
multi-object-tracking-paper-list
Paper list and source code for multi-object-tracking
NaveGo
NaveGo: an open-source MATLAB/GNU Octave toolbox for processing integrated navigation systems and performing inertial sensors analysis.
numpy-ml
Machine learning, in numpy
PythonRobotics
Python sample codes for robotics algorithms.
pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
road_graph_extraction_using_geometric_deep_learning
graph neural network approach for extracting road networks
RoadMarkingExtraction
A C++ Program for automatically extraction of road markings from MLS or ALS point cloud [ISPRS-A' 19]
RoadRunner
RoadRunner: improving the precision of road network inference from GPS trajectories
sort
Simple, online, and realtime tracking of multiple objects in a video sequence.
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
toulouse-road-network-dataset
Python code to generate the Toulouse Road Network dataset introduced in "Image-Conditioned Graph Generation for Road Network Extraction"
tracking-with-Extended-Kalman-Filter
Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors.
VPGNet
VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition (ICCV 2017)