Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery.

Santos J Núñez Jareño, Daniël P van Helden, Evgeny M Mirkes, Ivan Y Tyukin, Penelope M Allison

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

5 · Who and what money

Authors and funding

5 authors.

Santos J Núñez JareñoSchool of Mathematics and Actuarial Science, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0002-6134-1429

Daniël P van HeldenSchool of Archaeology and Ancient History, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0001-8365-2538

Evgeny M MirkesSchool of Mathematics and Actuarial Science, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0003-1474-1734

Ivan Y TyukinSchool of Mathematics and Actuarial Science, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0002-7359-7966

Penelope M AllisonSchool of Archaeology and Ancient History, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0001-6975-639X

Funding

Arts and Humanities Research Council AH/T001003/1

6 · The paper itself

Abstract

In this article, we consider a version of the challenging problem of learning from datasets whose size is too limited to allow generalisation beyond the training set. To address the challenge, we propose to use a transfer learning approach whereby the model is first trained on a synthetic dataset replicating features of the original objects. In this study, the objects were smartphone photographs of near-complete Roman

Indexed as

deep learningimage classificationlearning from scarce informationmachine learningRoman pottery (terra sigillata)simulated data

Identifiers

PMID34573765

DOI10.3390/e23091140

PMCPMC8469565

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.