论文标题
SpottheFake：在新的CNN增强式货物检测平台上的初步报告
SpotTheFake: An Initial Report on a New CNN-Enhanced Platform for Counterfeit Goods Detection
论文作者
论文摘要
伪造的商品贸易如今代表了整个世界贸易的3.3％以上，因此，这个问题现在比以往任何时候都需要更多的关注和可靠的解决方案，可以减少其对现代社会的负面影响。本文介绍了一个新颖的假冒商品检测平台的设计和早期开发，该平台利用了经典的VGG16经典学习能力，该模型通过“转移学习”过程和一个多阶段的伪造检测过程进行了训练，该过程被证明是可靠的，而且在实验中也很强大，我们已经在远处使用了各种图像，我们已经进行了各种图像。
The counterfeit goods trade represents nowadays more than 3.3% of the whole world trade and thus it's a problem that needs now more than ever a lot of attention and a reliable solution that would reduce the negative impact it has over the modern society. This paper presents the design and early stage development of a novel counterfeit goods detection platform that makes use of the outstsanding learning capabilities of the classical VGG16 convolutional model trained through the process of "transfer learning" and a multi-stage fake detection procedure that proved to be not only reliable but also very robust in the experiments we have conducted so far using an image dataset of various goods which we gathered ourselves.
