# Submissions for: Cone Detection for Formula Student Driverless Competition

|#| Submission | Links |
|-|-|-------------------------------------------|
|1|[Simulink Deep Learning Cone Detection for Formula Student Driverless](https://github.com/Chakradhara29/Cone-Detection-for-Formula-Student-Driverless-Competition-Assignment-MathWork)<br/> This project implements YOLO v2 deep learning for cone detection in a Formula Student driverless vehicle simulation using Simulink and the Vehicle Dynamics Blockset, with deployment to NVIDIA Jetson. <br><br> **Authors:** Amogha Chakradhara L <br/> **Affiliation:** Jain Deemed-to-be-University IIAEM <br> **Submission Date:** 2025-01-16|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/Chakradhara29/Cone-Detection-for-Formula-Student-Driverless-Competition-Assignment-MathWork) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=Chakradhara29/Cone-Detection-for-Formula-Student-Driverless-Competition-Assignment-MathWork) <br>  <br><br><br> [![Trend: Autonomous Vehicles](https://img.shields.io/badge/Trend-Autonomous%20Vehicles-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Autonomous%20Vehicles.md) [![Trend: Computer Vision](https://img.shields.io/badge/Trend-Computer%20Vision-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Computer%20Vision.md)|
|2|[Cone Detection for Formula Student Driverless Competition](https://github.com/DkPanseriya/Cone-Detection.git)<br/> This project uses MATLAB and Simulink to train a YOLOv2 object detection algorithm for identifying blue and yellow cones in a virtual environment, aiming to enhance autonomous Formula Student racing navigation. <br><br> **Authors:** Darshak Panseriya <br/> **Affiliation:** Technische Hochschule Ingolstadt <br> **Submission Date:** 2024-04-10|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/DkPanseriya/Cone-Detection.git) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=DkPanseriya/Cone-Detection) <br>  <br><br><br> [![Trend: Autonomous Vehicles](https://img.shields.io/badge/Trend-Autonomous%20Vehicles-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Autonomous%20Vehicles.md) [![Trend: Computer Vision](https://img.shields.io/badge/Trend-Computer%20Vision-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Computer%20Vision.md)|
|3|[YOLOv2-based Cone Detection for Formula Student Driverless](https://github.com/MahenderChoudhary/Cone-Detection-for-FSAE-Driverless/blob/406f4b9043fa47a48ff67ab32f523300ef0e680f/README.md)<br/> This project implements a YOLOv2-based computer vision system for real-time cone detection and tracking in Formula Student Driverless competitions, utilizing the FSOCO dataset and ROS. <br><br> **Authors:** Mahender Choudhary <br/> **Affiliation:** Fr. Conceicao Rodrigues College of Engineering <br> **Submission Date:** 2024-02-20|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/MahenderChoudhary/Cone-Detection-for-FSAE-Driverless/blob/406f4b9043fa47a48ff67ab32f523300ef0e680f/README.md) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=MahenderChoudhary/Cone-Detection-for-FSAE-Driverless) <br>  <br><br><br> [![Trend: Autonomous Vehicles](https://img.shields.io/badge/Trend-Autonomous%20Vehicles-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Autonomous%20Vehicles.md) [![Trend: Computer Vision](https://img.shields.io/badge/Trend-Computer%20Vision-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Computer%20Vision.md)|
|4|[Cone Detection for Formula Student Driverless Competition](https://github.com/pranavvgg/ConeDetection_FBDV_PranavGupta.git)<br/> A Matlab project for cone detection, processing video to identify cones on both sides of a Formula Student driverless car, with future GPU deployment planned for live camera feed. <br><br> **Authors:** Pranav Gupta, Pranav Gupta <br/> **Affiliation:** Thapar Institute of Engineering and Technology <br> **Submission Date:** 2024-02-20|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/pranavvgg/ConeDetection_FBDV_PranavGupta.git) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=pranavvgg/ConeDetection_FBDV_PranavGupta) <br>  <br><br><br> [![Trend: Autonomous Vehicles](https://img.shields.io/badge/Trend-Autonomous%20Vehicles-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Autonomous%20Vehicles.md) [![Trend: Computer Vision](https://img.shields.io/badge/Trend-Computer%20Vision-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Computer%20Vision.md)|
|5|[Cone Detection for Formula Student Driverless Competition](https://github.com/vivinvarshans/Cone-Detection-MathWork-Assignment.git)<br/> This project implements YOLOv2 cone detection using MATLAB and Simulink within a virtual Formula Student driverless environment for autonomous vehicle navigation. <br><br> **Authors:** Vivin Varshan S <br/> **Affiliation:** Vellore Institute of Technology, Vellore <br> **Submission Date:** 2023-12-24|<img width="400" height="0" style="display:block;line-height:0;border:none;" alt=""><br>[![GitHub Repo](https://img.shields.io/badge/GitHub-Repo-181717?style=flat&logo=github&logoColor=white)](https://github.com/vivinvarshans/Cone-Detection-MathWork-Assignment.git) <br> [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=vivinvarshans/Cone-Detection-MathWork-Assignment) <br>  <br><br><br> [![Trend: Autonomous Vehicles](https://img.shields.io/badge/Trend-Autonomous%20Vehicles-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Autonomous%20Vehicles.md) [![Trend: Computer Vision](https://img.shields.io/badge/Trend-Computer%20Vision-blue?style=flat)](https://github.com/mathworks/MathWorks-Excellence-in-Innovation/blob/main/megatrends/Computer%20Vision.md)|
