Developing advanced computer vision techniques for object detection and classification posed significant challenges, particularly for Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies. The key challenge was ensuring real-time detection accuracy under diverse environmental conditions, such as varying weather, lighting, and traffic scenarios.
The system needed to identify and classify objects like pedestrians, vehicles, and road signs with high precision while maintaining low latency. Integrating these capabilities into existing vehicle systems without compromising safety, performance, or scalability added further complexity to the project.
