Automobile Spare Part Classification via AI Image Processing Techniques, a Comparison Study

Artificial intelligence (AI) and image recognition technologies are developing rapidly, creating new opportunities for process improvement in industry, especially in spare parts classification. Spare parts classification using images has not been thoroughly researched and utilized in the car repair industry, especially in Malaysia. This project seeks to create a reliable and effective system that uses AI to identify and classify spare parts from user-uploaded images precisely. The main goals are to simplify inventory management and improve the precision and speed of part identification in diverse industrial environments. In the end, an accuracy of 98.70% was achieved for spare part type classification and $\mathbf{8 9. 7 0 \%}$ for both type and car brand classification with the use of transfer learning, finetuning, and object detection techniques.