| dc.contributor.author | Mallika Mehrotra, 22SCSE2030483 | |
| dc.contributor.author | Shubham Tripathi, 22SCSE2030036 | |
| dc.contributor.author | Prakash Kumar, 22SCSE2030039 | |
| dc.date.accessioned | 2024-09-17T04:10:45Z | |
| dc.date.available | 2024-09-17T04:10:45Z | |
| dc.date.issued | 2024-05 | |
| dc.identifier.uri | http://10.10.11.6/handle/1/17990 | |
| dc.description.abstract | YOLO v8, the most recent version of the well-liked object detection algorithm, is turning heads in the
realm of license plate detection (LPD), an essential step in automated number-plate recognition (ANPR)
systems. Let's examine the dynamic duo's collaboration: | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Galgotias University | en_US |
| dc.subject | Number | en_US |
| dc.subject | Plate | en_US |
| dc.subject | Detection | en_US |
| dc.title | “Number Plate Detection“ | en_US |
| dc.type | Technical Report | en_US |
