An algorithm to compare two-dimensional footwear outsole images using maximum cliques and speeded-up robust feature.

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

Who cites it

5 citing papers in PubMed.

1. A unified deep learning application framework for forensic shoeprint analysis under data-limited conditions.Scientific reports · 2026
   Article
2. FILNet: Fast Image-Based Indoor Localization Using an Anchor Control Network.Sensors (Basel, Switzerland) · 2023
   Article
3. Toward Developing Techniques─Agnostic Machine Learning Classification Models for Forensically Relevant Glass Fragments.Journal of chemical information and modeling · 2023
   Article
4. Location distribution of randomly acquired characteristics on a shoe sole.Journal of forensic sciences · 2022
   Article
5. An algorithm to compare two-dimensional footwear outsole images using maximum cliques and speeded-up robust feature.Statistical analysis and data mining · 2020
   Article

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

2 authors.

Funding

No grant is acknowledged in the PubMed record.

Abstract

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