Developing the Wheel Image Similarity Application with Deep Metric Learning: Hyundai Motor Company Case
DOI:
https://doi.org/10.1609/aaai.v37i13.26839Keywords:
Wheel Image Similarity, Hyundai Motor Company, Deep Metric LearningAbstract
The global automobile market experiences quick changes in design preferences. In response to the demand shifts, manufacturers now try to apply new technologies to bring a novel design to market faster. In this paper, we introduce a novel application that performs a similarity verification task of wheel designs using an AI model and cloud computing technology. At Jan 2022, we successfully implemented the application to the wheel design process of Hyundai Motor Company’s design team and shortened the similarity verification time by 90% to a maximum of 10 minutes. We believe that this study is the first to build a wheel image database and empirically prove that the cross-entropy loss does similar tasks as the pairwise losses do in the embedding space. As a result, we successfully automated Hyundai Motor’s verification task of wheel design similarity. With a few clicks, the end-users in Hyundai Motor could take advantage of our application.Downloads
Published
2023-09-06
How to Cite
Kang, K. P., Jeong, G. H., Eom, J. H., Kwon, S. B., & Park, J. H. (2023). Developing the Wheel Image Similarity Application with Deep Metric Learning: Hyundai Motor Company Case. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 15512-15518. https://doi.org/10.1609/aaai.v37i13.26839
Issue
Section
IAAI Technical Track on deployed Highly Innovative Applications of AI