Car logo recognition using YOLOv8 and microsoft azure custom vision
This research is conducted with its main objective to develop an accurate and faster model that can identify brands from logos captured through car images used by Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) staff. The software used for this case study is You Only Look Once (YOLO) version 8...
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| Format: | Conference or Workshop Item |
| Language: | English English |
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IEEE
2023
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/42512/1/Car_Logo_Recognition_using_YOLOv8_and_Microsoft_Azure_Custom_Vision.pdf http://umpir.ump.edu.my/id/eprint/42512/7/Car%20logo%20recognition%20using%20YOLOv8_ABST.pdf |
| _version_ | 1811138606476034048 |
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| author | Muhammad ‘Arif, Mohd Anuwa Nor Azuana, Ramli Mohd Zaid Waqiyuddin, Mohd Zulkifli |
| author_facet | Muhammad ‘Arif, Mohd Anuwa Nor Azuana, Ramli Mohd Zaid Waqiyuddin, Mohd Zulkifli |
| author_sort | Muhammad ‘Arif, Mohd Anuwa |
| collection | UMP |
| description | This research is conducted with its main objective to develop an accurate and faster model that can identify brands from logos captured through car images used by Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) staff. The software used for this case study is You Only Look Once (YOLO) version 8 and Microsoft Azure's Custom Vision. Each software was compared and results from the analysis showed that YOLOv8 is renowned for its speed and efficiency and is capable of real-time object detection, which makes it ideal for applications where speed is critical. However, this approach might occasionally compromise accuracy, especially for smaller objects or objects that are close together. Microsoft Azure Custom Vision, on the other hand, may not be as fast as YOLOv8, but it generally delivers high accuracy, especially if adequately trained with a diverse set of tagged images. To conclude, the choice between YOLOv8 and Microsoft Azure Custom Vision depends on the specific requirements of the project, technical expertise, and resources. |
| first_indexed | 2024-09-25T03:52:52Z |
| format | Conference or Workshop Item |
| id | UMPir42512 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-09-25T03:52:52Z |
| publishDate | 2023 |
| publisher | IEEE |
| record_format | dspace |
| spelling | UMPir425122024-09-06T03:22:57Z http://umpir.ump.edu.my/id/eprint/42512/ Car logo recognition using YOLOv8 and microsoft azure custom vision Muhammad ‘Arif, Mohd Anuwa Nor Azuana, Ramli Mohd Zaid Waqiyuddin, Mohd Zulkifli QA75 Electronic computers. Computer science This research is conducted with its main objective to develop an accurate and faster model that can identify brands from logos captured through car images used by Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) staff. The software used for this case study is You Only Look Once (YOLO) version 8 and Microsoft Azure's Custom Vision. Each software was compared and results from the analysis showed that YOLOv8 is renowned for its speed and efficiency and is capable of real-time object detection, which makes it ideal for applications where speed is critical. However, this approach might occasionally compromise accuracy, especially for smaller objects or objects that are close together. Microsoft Azure Custom Vision, on the other hand, may not be as fast as YOLOv8, but it generally delivers high accuracy, especially if adequately trained with a diverse set of tagged images. To conclude, the choice between YOLOv8 and Microsoft Azure Custom Vision depends on the specific requirements of the project, technical expertise, and resources. IEEE 2023 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42512/1/Car_Logo_Recognition_using_YOLOv8_and_Microsoft_Azure_Custom_Vision.pdf pdf en http://umpir.ump.edu.my/id/eprint/42512/7/Car%20logo%20recognition%20using%20YOLOv8_ABST.pdf Muhammad ‘Arif, Mohd Anuwa and Nor Azuana, Ramli and Mohd Zaid Waqiyuddin, Mohd Zulkifli (2023) Car logo recognition using YOLOv8 and microsoft azure custom vision. In: 4th International Conference on Data Analytics for Business and Industry, ICDABI 2023 , 25 - 27 October 2023 , Bahrain. 477 -481.. ISBN 979-835036978-6 (Published) https://doi.org/10.1109/ICDABI60145.2023.10629291 |
| spellingShingle | QA75 Electronic computers. Computer science Muhammad ‘Arif, Mohd Anuwa Nor Azuana, Ramli Mohd Zaid Waqiyuddin, Mohd Zulkifli Car logo recognition using YOLOv8 and microsoft azure custom vision |
| title | Car logo recognition using YOLOv8 and microsoft azure custom vision |
| title_full | Car logo recognition using YOLOv8 and microsoft azure custom vision |
| title_fullStr | Car logo recognition using YOLOv8 and microsoft azure custom vision |
| title_full_unstemmed | Car logo recognition using YOLOv8 and microsoft azure custom vision |
| title_short | Car logo recognition using YOLOv8 and microsoft azure custom vision |
| title_sort | car logo recognition using yolov8 and microsoft azure custom vision |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/42512/1/Car_Logo_Recognition_using_YOLOv8_and_Microsoft_Azure_Custom_Vision.pdf http://umpir.ump.edu.my/id/eprint/42512/7/Car%20logo%20recognition%20using%20YOLOv8_ABST.pdf |
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