DEEP LEARNING – BASED VEHICLE DAMAGE ASSESSMENT SYSTEM

DEEP LEARNING – BASED VEHICLE DAMAGE ASSESSMENT SYSTEM 1D. Madhuri,2Damarla Keerthi,3Bapatla Chandini,4Dasari Rajeswari 03 08 Vehicle damage assessment is an essential process in automobile insurance and repair services Traditional inspection methods are manual timeconsuming and prone to errors This paper presents a Deep LearningBased Vehicle Damage Assessment System that uses the YOLO You Only Look Once object detection algorithm to automatically detect and classify vehicle damages such as dents scratches broken glass and bumper damage from uploaded images Developed using Python Flask OpenCV TensorFlowKeras and SQLite the system provides fast accurate and reliable damage detection by highlighting damaged regions with bounding boxes and labels It reduces inspection time minimizes human intervention and supports efficient insurance claim processing and repair estimation making it a practical solution for intelligent vehicle damage assessment

2026