The main goal of the project was to build a solution to identify a brand-specific style using images as a data source. Style is defined as a well-known color scheme, image composition and anything that may help one to affiliate an image with some brand. For example, with the BMW trademark. In other words, we were faced with the task of classifying images.
We have successfully built a model that steadily copes with its purpose. The accuracy value for our classification is 95% on the test data. In the future, with the appearance of new data (new BMW advertising campaigns, for example), it will also be possible to train a model on these images and improve neural network accuracy.
Such a solution could help young specialists in the Product design area with making sure their own projects are not plagiarizing any unique traits of well-known brands and are distinctive enough on its own.
It can also help young designers with finding out what well-known brands had the most influence when the new style was developed.
It can also help product design students to get acquainted more with some distinctive elements of branding for a better understanding of how to make their own projects more recognizable.
To put it simple, that solution could be used as ML for plagiarism search engines.