- Title
- Exploring the Incremental Improvements of YOLOv7 over YOLOv5 for Character Recognition
- Creator
- Boby, Alden, Brown, Dane L, Connan, James, Marais, Marc
- Subject
- To be catalogued
- Date
- 2022
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/463395
- Identifier
- vital:76405
- Identifier
- xlink:href="https://link.springer.com/chapter/10.1007/978-3-031-35644-5_5"
- Description
- Technological advances are being applied to aspects of life to improve quality of living and efficiency. This speaks specifically to automation, especially in the industry. The growing number of vehicles on the road has presented a need to monitor more vehicles than ever to enforce traffic rules. One way to identify a vehicle is through its licence plate, which contains a unique string of characters that make it identifiable within an external database. Detecting characters on a licence plate using an object detector has only recently been explored. This paper uses the latest versions of the YOLO object detector to perform character recognition on licence plate images. This paper expands upon existing object detection-based character recognition by investigating how improvements in the framework translate to licence plate character recognition accuracy compared to character recognition based on older architectures. Results from this paper indicate that the newer YOLO models have increased performance over older YOLO-based character recognition models such as CRNET.
- Format
- computer, online resource, application/pdf, 1 online resource (15 pages), pdf
- Publisher
- SpringerLink
- Language
- English
- Relation
- International Advanced Computing Conference, Boby, A., Brown, D., Connan, J. and Marias, M., 2022, December. Exploring the Incremental Improvements of YOLOv7 over YOLOv5 for Character Recognition. In International Advanced Computing Conference (pp. 50-65). Cham: Springer Nature Switzerland, International Advanced Computing Conference p. 50 2022 1865-0937
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the SpringerLink Terms of Use Statement ( https://link.springer.com/termsandconditions)
- Rights
- Closed Access
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