Hello everyone,
I’m looking for help in finding some reading material on the topic of classifying an image based on its proximity to a reference image. I’m working on a project just now where I try to separate cat & dog images based on their cosine similarities. I’m now getting an accuracy of about 98.5% on a small validation set by using Resnet18.
The way that it works (briefly) is that I compute embeddings for an unknown image and checks it cosine similarity against a bunch of dog & cat reference images. If the unknown image matches better with the dog reference images, I’ll classify the unknown image as a dog.
The closest method I can think of is e.g. identifying people via triplet loss. I also know there are fields such as image matching or image retrieval that tangent the subject.
I’m looking for resources or people willing to discuss the subject of classifying a data point in accordance to its proximity with other similar data points.