A test simulation of all projects and models from time to time.
-
Updated
Jul 2, 2024 - Python
A test simulation of all projects and models from time to time.
Python3 modul and cli to controll the Cleware traffic light
Optimize traffic flow at intersections with a Deep Q-Learning agent. Utilizes reinforcement learning to control traffic signals efficiently.
ImVisible: Pedestrian Traffic Light (PTL) Dataset, Lightweight CNN (LytNet), and Mobile Application for the Visually Impaired (CAIP '19, ICCV Workshops '19)
Traffic light recognition
Traffic Light Project: Implementing real-time traffic density calculation and object detection using YOLOv3-tiny. Seeking to enhance car detection accuracy with a curated dataset from Zenodo.
Control a traffic light via HTML using a Raspberry and a 4 channel relay.
Manage traffic by controlling traffic lights to pass all the cars
Using Deep Q-Network agent to optimize a traffic signal at a single intersection
A simple yet effective repo for object detection based on the FCOS architecture.
Module for detecting traffic lights in the CARLA autonomous driving simulator. Based on the YOLO v2 deep learning object detection model and implemented in keras, using the tensorflow backend.
OpenLendaのPythonでのONNX推論サンプル
RPiP9 把 Raspberry Pi 上常見的模組搜集而成。
An advanced traffic management system (TMS) is a context-aware solution that relies on real-time data from connected road infrastructure and predictive analytics to effectively coordinate traffic across city arteries.
Traffic Light Reinforcement Learning
🎓Repository for masters labs on FCSN, BSUIR
In this project, 4 different YOLOv3 models with different accuracy in different FPS values were created in the image processing area. The YOLOv3 models used are YOLOv3-tiny, YOLOv3-320, YOLOv3-416 and YOLOv3-618, respectively.
Add a description, image, and links to the traffic-light topic page so that developers can more easily learn about it.
To associate your repository with the traffic-light topic, visit your repo's landing page and select "manage topics."