Identification of similar design principles of passenger cars using deep neural networks

摘要

This paper demonstrates the idea of using deep neural networks to identify similar design principles. It is shown how a neural network originally trained to classify the images of cars to their respective brands, can also be used to identify car models following similar design principles across different brands. The proposed approach involves a comprehensive error analysis on the predictions of the deep neural network to draw inferences about design similarities of car models produced by different manufacturers. Several examples of car models following close design patterns across different brands are identified using this approach.