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3duis

511-cctv-camera-vehicle-detection-and-tracking-using-stmap-and-daiu-net

VEHICLE DETECTION AND TRACKING FOR 511 TRAFFIC CAMERAS WITH DAIU AND STMAP

ab3dmot

(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

agile_autonomy

Repository Containing the Code associated with the Paper: "Learning High-Speed Flight in the Wild"

allanlab

Allan Lab website

artificial-intelligence-class.github.io

atspm

Automated Traffic Signal Performance Measures (ATSPM) are a series of visual aids that display the high-resolution data from signal controllers. They are a valuable asset management tool, aiding personnel in the control of both signal hardware and signal timing and coordination. They allow analysis of data collected 24 hours a day, 7 days a week, improving the accuracy, flexibility, and performance of signal equipment and the system as a whole. ATSPM are used to optimize mobility, manage traffic signal timing and maintenance, reduce congestion, save fuel costs and improve safety.

atspm-1

Automated Traffic Signal Performance Measures (ATSPM) are a series of visual aids that display the high-resolution data from signal controllers. They are a valuable asset management tool, aiding personnel in the control of both signal hardware and signal timing and coordination. They allow analysis of data collected 24 hours a day, 7 days a week, improving the accuracy, flexibility, and performance of signal equipment and the system as a whole. ATSPM are used to optimize mobility, manage traffic signal timing and maintenance, reduce congestion, save fuel costs and improve safety.

awesome-computer-vision

A curated list of awesome computer vision resources

big-data-analytics-for-network-level-travel-time-prediction

ctm_matlab

Implementation of Cell-Transmission Model in plateform of MATLAB

databook_python

IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz

deep-turbulence

Multi-fidelity Generative Deep Learning Turbulent Flows

driving-irl-ngsim

(T-ITS) Driving Behavior Modeling using Naturalistic Human Driving Data with Inverse Reinforcement Learning

drone_video_stabilization_analysis

dronevehicle

Drone based RGBT Vehicle Detection and Counting: A Challenge

dste_ngsm_validation_refinement

final-project-team-17-jobs-markets

final-project-team-17-jobs-markets created by GitHub Classroom

flow

Computational framework for reinforcement learning in traffic control

hash-based-gaussian-mixture-model-for-roadside-lidar-smart-mobility-application

image-stitching-panorama

Computer Vision Project, stitching different perspective images into a single smooth panorama using Laplacian Blending.

imtsl

IMTSL - Incremental and Multi-feature Tensor Subspace Learning

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.

lidar-point-cloud-preprocessing-matlab

Pre-processing Technique of LIDAR PCD Data Using KITTI-Dataset

machine-learning-and-simulation

All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)

multiresolutiongail_baselines

Hierarchical Multiscale Recurrent Neural Network and Clockwork RNN implementations as baselines for comparison to a Multiresolution GAIL algorithm.

ngsim-star-reconstructed-good-next-generation-simulation-trajectory-dataset-

ngsim_data_processing

DATA PROCESSING FOR NGSIM (Car Following)

ngsim_env

Learning human driver models from NGSIM data with imitation learning.