Deep learning-based real-time pothole detection for avoiding road accident
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Ձևաչափ: | Թեզիս |
| Լեզու: | English |
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Brac University
2022
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| Առցանց հասանելիություն: | http://hdl.handle.net/10361/17354 |
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10361-173542022-09-27T21:02:19Z Deep learning-based real-time pothole detection for avoiding road accident Basher, Rafsan Ayon, Asif Raihan Gharamy, Avijit Zayed, Abdullah Al Zaman, Md Samin Yeasar Ibna Uddin, Jia Ashraf, Faisal Bin Department of Computer Science and Engineering, Brac University Road Pothole Deep learning Image processing Real-time MobileNet Inception- v3 YOLOv5 Deep learning (Machine learning) Image processing -- Digital techniques. Cognitive learning theory (Deep learning) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 33-36). Bangladesh is a fast-developing country, and the number of roads increasing with it is immense. With the ever-growing amount of road comes the age-old problem of a pothole. This paper represents a model of deep learning-based, real-time pothole detection for finding and avoiding road accidents. Any types of image processingbased detection, in this case, pothole detection, are done through various steps. For example, collecting data sets is one of the most crucial steps to create any recognition system. Labeling an image means pinpointing the subject which we will be trying to find. Training the algorithm through those images to detect the subjects is critical in detecting potholes. In this research paper, to detect potholes from real-time videos, firstly, we collected data sets containing more than 600 images of potholes. After that, we labeled those images through labeling software. Then in chapter-1 we used those images to train the model (MobileNet, Inception-v3) which was detecting potholes from still photos given to it. Next, we used YOLOv5 to detect potholes from real-time feeds. In this proposed system, by using the real-time feed, potholes will be detected. Moreover, this will help the masses to detect potholes on roads to avoid accidents, and it will also help people related to the road works to find the potholes for further road maintenance. Rafsan Basher Asif Raihan Ayon Avijit Gharamy Abdullah Al Zayed Md Samin Yeasar Ibna Zaman B. Computer Science and Engineering 2022-09-27T07:31:07Z 2022-09-27T07:31:07Z 2022 2022-01 Thesis ID 17301042 ID 17301170 ID 19101519 ID 17301126 ID 17101533 http://hdl.handle.net/10361/17354 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 36 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Road Pothole Deep learning Image processing Real-time MobileNet Inception- v3 YOLOv5 Deep learning (Machine learning) Image processing -- Digital techniques. Cognitive learning theory (Deep learning) |
| spellingShingle |
Road Pothole Deep learning Image processing Real-time MobileNet Inception- v3 YOLOv5 Deep learning (Machine learning) Image processing -- Digital techniques. Cognitive learning theory (Deep learning) Basher, Rafsan Ayon, Asif Raihan Gharamy, Avijit Zayed, Abdullah Al Zaman, Md Samin Yeasar Ibna Deep learning-based real-time pothole detection for avoiding road accident |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Uddin, Jia |
| author_facet |
Uddin, Jia Basher, Rafsan Ayon, Asif Raihan Gharamy, Avijit Zayed, Abdullah Al Zaman, Md Samin Yeasar Ibna |
| format |
Thesis |
| author |
Basher, Rafsan Ayon, Asif Raihan Gharamy, Avijit Zayed, Abdullah Al Zaman, Md Samin Yeasar Ibna |
| author_sort |
Basher, Rafsan |
| title |
Deep learning-based real-time pothole detection for avoiding road accident |
| title_short |
Deep learning-based real-time pothole detection for avoiding road accident |
| title_full |
Deep learning-based real-time pothole detection for avoiding road accident |
| title_fullStr |
Deep learning-based real-time pothole detection for avoiding road accident |
| title_full_unstemmed |
Deep learning-based real-time pothole detection for avoiding road accident |
| title_sort |
deep learning-based real-time pothole detection for avoiding road accident |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/17354 |
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AT basherrafsan deeplearningbasedrealtimepotholedetectionforavoidingroadaccident AT ayonasifraihan deeplearningbasedrealtimepotholedetectionforavoidingroadaccident AT gharamyavijit deeplearningbasedrealtimepotholedetectionforavoidingroadaccident AT zayedabdullahal deeplearningbasedrealtimepotholedetectionforavoidingroadaccident AT zamanmdsaminyeasaribna deeplearningbasedrealtimepotholedetectionforavoidingroadaccident |
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