Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

DHI-GAN: Improving Dental-Based Human Identification Using Generative Adversarial Networks.

Yi Lin, Fei Fan, Jianwei Zhang

    IEEE Transactions on Neural Networks and Learning Systems
    |March 25, 2022
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Age estimation from pubic symphysis based on cinematic volume rendering: comparison between Suchey-Brooks staging and deep learning.

    International journal of legal medicine·2026
    Same author

    Sex and social group altered the gut microbiome and fecal metabolome in the critically endangered Yangtze finless porpoise (<i>Neophocaena asiaeorientalis asiaeorientalis</i>).

    Current zoology·2026
    Same author

    Fingerprint Spectral Inversion-Enabled Terahertz Metasurface for Multidimensional Detection of Trace Antibiotics.

    ACS sensors·2026
    Same author

    Global burden of bipolar disorder in 204 countries and territories, 1990-2021: a systematic analysis of temporal trends, demographic disparities, and SDI associations for the Global Burden of Disease Study 2021.

    Psychiatry research·2026
    Same author

    Chromium-Catalyzed Direct Conversion of Ethers to Aryl-Substituted Alkenes.

    Organic letters·2026
    Same author

    Amelioration of tic disorder by Jujuboside A via gut microbiota remodeling and intestinal 5-HT signaling.

    Frontiers in neuroscience·2026

    A new semisupervised framework, DHI-GAN, improves dental-based human identification (DHI) with limited data. This generative adversarial network (GAN) approach enhances accuracy by generating and classifying dental features effectively.

    Area of Science:

    • Forensic Science
    • Biometrics
    • Artificial Intelligence

    Background:

    • Dental-based human identification (DHI) faces challenges with small sample sizes.
    • Accurate identification is crucial in forensic and biometric applications.

    Purpose of the Study:

    • To propose a novel semisupervised framework to address the small-sample problem in DHI.
    • To enhance DHI performance using a "classifying while generating" paradigm with a generative adversarial network (GAN).

    Main Methods:

    • Developed DHI-GAN, a generative adversarial network incorporating an additional classifier for efficient training.
    • Implemented an identity embedding-guided architecture and a parallel spatial and channel fusion attention block for feature learning.
    • Utilized a combination of ArcFace and focal loss, with parameters to control generated samples during optimization.

    Related Experiment Videos

    Main Results:

    • The DHI-GAN framework achieved a top-one accuracy rate of 92.5% on a real-world dataset.
    • Outperformed existing baseline methods in dental-based human identification.
    • Demonstrated the effectiveness of the GAN-based semisupervised strategy in reducing the need for extensive training data.

    Conclusions:

    • The proposed DHI-GAN framework offers a powerful solution for small-sample DHI.
    • The semisupervised training strategy can be integrated with other classification models.
    • This approach significantly advances the field of forensic biometrics.