Summary of Localization Of Synthetic Manipulations in Western Blot Images, by Anmol Manjunath et al.
Localization of Synthetic Manipulations in Western Blot Images
by Anmol Manjunath, Viola Negroni, Sara Mandelli, Daniel Moreira, Paolo Bestagini
First submitted to arxiv on: 25 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Multimedia (cs.MM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a synthetic detector for localizing manipulations in Western blot images, which is essential for maintaining the integrity of digital content and societal trust. The detector operates on small image patches, aggregating patch contributions to estimate a tampering heatmap that highlights synthetic pixels. This methodology proves effective when tested over two manipulated Western blot datasets and an external dataset of scientific images with different semantics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper finds ways to spot fake images in science publications. Fake images can be very realistic and are made using advanced computer tools. The researchers developed a way to detect these fake areas by looking at small parts of the image, called patches. They then combined the information from these patches to create a map that shows where the fake parts are. This method worked well when tested on several sets of images, including some that were changed automatically and others that were edited by hand. |
Keywords
» Artificial intelligence » Semantics
