Real-time object detection by cameras mounted on mobile robots on campus

Real-time object detection by cameras mounted on mobile robots on campus

This dissertation aims to identify and apply campus popularization objectives and strengthen campus management and security. Because most of the detection is for vehicles and pedestrians which often requires high accuracy and real-time performance. This dissertation uses the YOLOv5 algorithm, which...

Full description

Saved in:
Bibliographic Details
Main Author: Xu, Haozhe
Other Authors: Zheng Yuanjin
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2025
Subjects:
Engineering
Object detection
YOLOv5
Online Access:https://hdl.handle.net/10356/182176
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-182176
record_format dspace
spelling sg-ntu-dr.10356-1821762025-01-13T07:12:44Z Real-time object detection by cameras mounted on mobile robots on campus Xu, Haozhe Zheng Yuanjin School of Electrical and Electronic Engineering YJZHENG@ntu.edu.sg Engineering Object detection YOLOv5 This dissertation aims to identify and apply campus popularization objectives and strengthen campus management and security. Because most of the detection is for vehicles and pedestrians which often requires high accuracy and real-time performance. This dissertation uses the YOLOv5 algorithm, which realizes real-time object detection. After big data training, the feasibility and accuracy of the algorithm are guaranteed, and the most effective model is determined. Finally, the camera is mounted on the robot to realize dynamic detection. In addition, some feasible solutions are also put forward to solve some problems encountered in the detection process. Master's degree 2025-01-13T07:12:44Z 2025-01-13T07:12:44Z 2024 Thesis-Master by Coursework Xu, H. (2024). Real-time object detection by cameras mounted on mobile robots on campus. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/182176 https://hdl.handle.net/10356/182176 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Object detection
YOLOv5
spellingShingle Engineering
Object detection
YOLOv5
Xu, Haozhe
Real-time object detection by cameras mounted on mobile robots on campus
description This dissertation aims to identify and apply campus popularization objectives and strengthen campus management and security. Because most of the detection is for vehicles and pedestrians which often requires high accuracy and real-time performance. This dissertation uses the YOLOv5 algorithm, which realizes real-time object detection. After big data training, the feasibility and accuracy of the algorithm are guaranteed, and the most effective model is determined. Finally, the camera is mounted on the robot to realize dynamic detection. In addition, some feasible solutions are also put forward to solve some problems encountered in the detection process.
author2 Zheng Yuanjin
author_facet Zheng Yuanjin
Xu, Haozhe
format Thesis-Master by Coursework
author Xu, Haozhe
author_sort Xu, Haozhe
title Real-time object detection by cameras mounted on mobile robots on campus
title_short Real-time object detection by cameras mounted on mobile robots on campus
title_full Real-time object detection by cameras mounted on mobile robots on campus
title_fullStr Real-time object detection by cameras mounted on mobile robots on campus
title_full_unstemmed Real-time object detection by cameras mounted on mobile robots on campus
title_sort real-time object detection by cameras mounted on mobile robots on campus
publisher Nanyang Technological University
publishDate 2025
url https://hdl.handle.net/10356/182176
_version_ 1821237218159624192

Similar Items