- cross-posted to:
- hackernews@derp.foo
- cross-posted to:
- hackernews@derp.foo
An algorithm that takes just seconds to scan a paper for duplicated images racks up more suspicious images than a person.
An algorithm that takes just seconds to scan a paper for duplicated images racks up more suspicious images than a person.
Better accuracy usually (but not granted if badly implemented)
Better accuracy than what? What the article describes is fairly basic image processing. The whole thing could be done with like a dozen lines of Python.
In Image classification. Neural-network-based ML methods can have greater accuracy than alternative options in image classification
For classification, sure. But based on the article that’s not what they were doing here. This was just comparing an image to a bunch of other images to see if it was the same.
To see if they are similar. They are not interested to see if the image is the same but to understand if the message is the same, to the level that it is a fraud, not simple citation. They are flagging frauds…
I have no idea how they do it, and I strongly believe it is an overkill given that the credibility of published research is low due to the mafia-like academic system, not because of few frauds.