Do you want to try out the method with your own images? Here is our free demo application. huggingface.co/spaces/ciass...

The novelty of this method is that it provides new insights for comparative politics: While persons, flags and signboard are important objects in protest images, particular features of protest differ across countries and protest episodes. Our method can detect these.

Our method detects objects present in images, creates feature vectors from those objects and uses them as input for machine learning classifiers. We tested this on a new dataset of 140k images to predict which ones show protest. The accuracy is roughly on par with popular CNNs.

While existing classifiers for images reach high levels of accuracy, it is difficult to systematically assess the visual features on which they base their classification. This problem is especially pressing for complex images that contain many different types of objects.