Russian Federation
This article presents the development of a novel method for identifying repair impacts on vehicle spare parts during automotive commodity research examinations.
vehicle technical expertise, damage assessment, spare parts, repair identification, machine learning
1. Metodicheskie rekomendacii po provedeniyu sudebnyh avtotehnicheskih ekspertiz i issledovaniy kolesnyh transportnyh sredstv v celyah opredeleniya razmera uscherba, stoimosti vosstanovitel'nogo remonta i ocenki. M.: FBU RFRCSE pri Minyuste Rossii, 2018 g.
2. Namam A. Mohammed, Moayad Y. Potrus, Abbas M. Ali. Deep Learning Based Car Damage Classificationand Cost Estimation / ZANCOJournal of Pure and Applied SciencesThe official scientific journal of Salahaddin University-Erbil // ZJPAS: 2023, 35(1): 1-9 URL:https://zancojournal.su.edu.krd/index.php/JPAS/article/view/303/236.
3. R.E. van Ruitenbeek. S. Bhulai. Convolutional Neural Networks for vehicle damage detection / Machine Learning with Applications Volume 9, 15 September 2022 - URL:https://www.sciencedirect.com/science/article/pii/S2666827022000433?pes=vor&utm_source=wiley&getft_integrator=wiley#b9.
4. Panumate Chetprayoon, Miki Katsuragi URL:https://cloud.google.com/blog/products/ai-machine-learning/identifying-vehicle-damage-effectively-with-explainable-ai.
5. Md Jahid Hasan, Cong Kha Nguyen, Yee Ling Boo, Hamed Jahani, Kok-Leong Ong. Vehicle Damage Detection Using Artificial Intelligence: A Systematic Literature Review. URL:https://wires.onlinelibrary.wiley.com/doi/full/10.1002/widm.70027
6. Evtyukov S. A., Vasil'ev Ya. V. Rekonstrukciya i ekspertiza DTP v primerah. SPb.: Izdatel'skiy dom Petropolis, 2012. 323 s.
7. Evtyukov S. A., Vasil'ev Ya. V. Ekspertiza DTP: metody i tehnologii. SPb., SPbGASU. 2012. 310 s.



