Project information

• Category: User Experience, Machine Learning, Image classification
• Project URL: Report

This research focuses on using image classification to improve the objective analysis of design trends, particularly in the automotive industry. By evaluating correlations between classifiers and datasets, the study aims to reduce subjectivity and enhance the identification of new product trends while preserving brand DNA. Using machine learning tools like Weka, the research compares different classifiers to find the best approach for classifying car models based on brand name and DNA.

The analysis involved categorizing car images from an online catalog, focusing on wagon models from Audi, BMW, Chevrolet, and Lexus between 2017 and 2022. Results showed that classifiers like SMO and Logistics provided high accuracy, revealing significant patterns in brand identity and product development.

This study offers valuable insights for designers and customers, helping them understand brand characteristics and make informed decisions about emerging market trends.