Trying to spot a real Chanel from a fake? Deep learning tech can help

by 8:30 PM 0 comments
Given the ubiquity of fakes among re-sellers, buyers often examine pre-owned fashion to deduce authenticity, often analyzing the stitching, font size and interior labels.
But sometimes, a copy is just so well-made that the human eye can`t tell it from the original.
That`s where technology can help.
Entrupy is a portable scanning device that instantly detects imitation designer bags by taking microscopic pictures that take into account details of the material, processing, workmanship, serial number, and wear/tear.
It then employs the technique of deep learning to compare the images against a vast database that includes top luxury brands and if the bag is deemed authentic, users immediately get a Certificate of Authenticity.
After launching as a paid service in September 2016, the New York-based venture now has over 130 paid customers, almost all of whom are American businesses drawn to the 97.
1 percent accuracy rate, explained Entrupy CEO Vidyuth Srinivasan.
Other investors include New York University, deep learning pioneer Yann LeCun, and Japanese venture capital firm Accord Ventures.
"We`re choosing to start with second-hand re-sellers initially as we see a huge lack of trust in the luxury goods space, especially online," Srinivasan told CNBC.
In 2015, Singapore-based e-tailer The Fifth Collection, which specializes in secondhand luxury fashion, became one of Entrupy`s early investors.
At the time, founders Nejla Matam-Finn and Michael Finn were self-funding The Fifth Collection and hadn`t even paid themselves a salary but they called the Entrupy investment a no-brainer.

Dramelin

Developer

Cras justo odio, dapibus ac facilisis in, egestas eget quam. Curabitur blandit tempus porttitor. Vivamus sagittis lacus vel augue laoreet rutrum faucibus dolor auctor.

0 comments:

Post a Comment