Abstract
This paper presents a preliminary study on the automatic detection of compliance with predefined standards for vehicles in delivery fleets. The aim is to minimise the dependency of human labour in determining whether different brand/model vehicles used by Yurtiçi Kargo Servisi AŞ during distribution services meet the company's standards. For this purpose, images of the company's vehicles taken from four different angles are uploaded to the system and analysed by a YOLOv11-based model. The model has been trained with different versions of YOLOv11 and the test results obtained are reported. The model detects the presence of a vehicle in each image, determines its orientation (if present), and identifies the company logo or small logo on the vehicle. Studies on the detection of other requirements of vehicle standards (fading, deterioration, logo compliance, etc.) are ongoing.
| Translated title of the contribution | Automated Visual Inspection System for Validation of Company Vehicle Standards in Delivery Fleets |
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| Original language | Turkish |
| Title of host publication | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798331566555 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Istanbul, Turkey Duration: 25 Jun 2025 → 28 Jun 2025 |
Publication series
| Name | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 - Proceedings |
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Conference
| Conference | 33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025 |
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| Country/Territory | Turkey |
| City | Istanbul |
| Period | 25/06/25 → 28/06/25 |
Bibliographical note
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