Abstract:
Cars are an essential part of modern life, providing people with a convenient and efficient means of transportation. Cars have also had a significant impact on society, contributing to the growth of the automotive industry and enabling people to travel for shorter periods of time. In recent years, the development of computer vision technologies has changed the way cars are identified, making it faster, and more accurate. To stay ahead of the competition in the constantly evolving automobile business, consistent adaptation is necessary. Identifying the make and model of a vehicle and assessing its commonalities with other cars are two of the biggest hurdles that manufacturers and service centers have to tackle. When working with big databases of car photos and specifications, this approach can be time-consuming and error-prone. We have proposed a project that aims to develop software that can recognize the make and model of a vehicle and check its commonality with other vehicles of the same Type. Deep learning techniques will be used by the software to analyze photos as well as live images of cars and detect important characteristics like size, wheelbase, and body shape.
The solution will be able to analyze huge datasets of car images to find vehicle types and common design features across various models. It can help manufacturers and repair shops identify and track common car parts. The solution will be adaptable to meet specific industry and organizational requirements.
The proposed solution will have significant benefits for the automotive industry, ultimately leading to increased efficiency and improved customer satisfaction.
