Evidence map›Paper›PMID 35808507›Full record

ArticleSensors (Basel, Switzerland)2022

Thermal-Visible Face Recognition Based on CNN Features and Triple Triplet Configuration for On-the-Move Identity Verification.

Marcin Kowalski, Artur Grudzień, Krzysztof Mierzejewski

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

3 authors.

Marcin KowalskiInstitute of Optoelectronics, Military University of Technology, Gen. S. Kaliskiego, 00-908 Warsaw, Poland.ORCID 0000-0002-1361-9828
Artur GrudzieńInstitute of Optoelectronics, Military University of Technology, Gen. S. Kaliskiego, 00-908 Warsaw, Poland.ORCID 0000-0002-2641-8419
Krzysztof MierzejewskiFaculty of Cybernetics, Military University of Technology, Gen. S. Kaliskiego, 00-908 Warsaw, Poland.ORCID 0000-0002-5172-8419

Funding

This project has received funding from the European Union's Horizon 2020 research and innova-tion programme under grant agreement No 833704 833704
6 · The paper itself

Abstract

Face recognition operating in visible domains exists in many aspects of our lives, while the remaining parts of the spectrum including near and thermal infrared are not sufficiently explored. Thermal-visible face recognition is a promising biometric modality that combines affordable technology and high imaging qualities in the visible domain with low-light capabilities of thermal infrared. In this work, we present the results of our study in the field of thermal-visible face verification using four different algorithm architectures tested using several publicly available databases. The study covers Siamese, Triplet, and Verification Through Identification methods in various configurations. As a result, we propose a triple triplet face verification method that combines three CNNs being used in each of the triplet branches. The triple triplet method outperforms other reference methods and achieves TAR @FAR 1% values up to 90.61%.

Indexed as

Biometric IdentificationFacial RecognitionAlgorithmsFaceImage Processing, Computer-AssistedbiometricsCNNcross-spectral face recognitionthermal to visible face recognition

Identifiers

PMID35808507
PMCPMC9269800

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.