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Publicatie

Deep Diamond Re-ID

Boekbijdrage - Boekhoofdstuk Conferentiebijdrage

Re-identification neural networks are widely used in numerous applications such as crowd control, crime investi- gations, safety systems and even in most smartphones to unlock the phone with a picture of the owner. These techniques are mostly used to re-identify faces or persons but in this paper we investigate the possibility to adapt these to also re-identify similar looking objects such as diamonds. Since polished diamonds are very similar to the naked eye, it is difficult to distinguish one diamond from another. We have indications that diamonds are sometimes switched by trained switchers with fake or less expensive stones, while they pretend to inspect the stone. A solution to this is diamond fingerprinting. We therefore propose a technique to generate a unique ID for each stone, which allows to re-identify the diamond solely based on an image of the gem. Since each diamond is assigned a unique ID it is even possible to keep track of the diamonds over time. This allows the seller to verify his stones before and after trading while switchers don’t stand a chance. For this task we trained and adapted a classification network optimized for both speed and accuracy.
Boek: 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)
Pagina's: 2020 - 2025
ISBN:978-1-7281-4550-1
Jaar van publicatie:2020
Toegankelijkheid:Open