Onalaja Joshua, Shahra Essa Q, Basurra Shadi, Jabbar Waheb A
Faculty of Computing, Engineering and Built Environment, Birmingham City University, Birmingham B4 7RQ, UK.
Sensors (Basel). 2024 May 10;24(10):3030. doi: 10.3390/s24103030.
The sneaker industry is continuing to expand at a fast rate and will be worth over USD 120 billion in the next few years. This is, in part due to social media and online retailers building hype around releases of limited-edition sneakers, which are usually collaborations between well-known global icons and footwear companies. These limited-edition sneakers are typically released in low quantities using an online raffle system, meaning only a few people can get their hands on them. As expected, this causes their value to skyrocket and has created an extremely lucrative resale market for sneakers. This has given rise to numerous counterfeit sneakers flooding the resale market, resulting in online platforms having to hand-verify a sneaker's authenticity, which is an important but time-consuming procedure that slows the selling and buying process. To speed up the authentication process, Support Vector Machines and a convolutional neural network were used to classify images of fake and real sneakers and then their accuracies were compared to see which performed better. The results showed that the CNNs performed much better at this task than the SVMs with some accuracies over 95%. Therefore, a CNN is well equipped to be a sneaker authenticator and will be of great benefit to the reselling industry.
运动鞋行业正持续快速扩张，未来几年其市值将超过1200亿美元。这在一定程度上得益于社交媒体和在线零售商围绕限量版运动鞋的发布制造热潮，这些限量版运动鞋通常是全球知名偶像与鞋类公司的合作款。这些限量版运动鞋通常通过在线抽奖系统少量发售，这意味着只有少数人能够买到。不出所料，这使得它们的价值飙升，并为运动鞋创造了一个利润极其丰厚的转售市场。这导致大量假冒运动鞋充斥转售市场，使得在线平台不得不人工核实运动鞋的真伪，这是一个重要但耗时的过程，减缓了买卖流程。为了加快认证过程，支持向量机和卷积神经网络被用于对真假运动鞋的图像进行分类，然后比较它们的准确率，以确定哪种方法表现更佳。结果表明，卷积神经网络在这项任务中的表现比支持向量机好得多，有些准确率超过了95%。因此，卷积神经网络完全有能力成为运动鞋真伪鉴定工具，这将对转售行业大有裨益。
