A Deep Learning Approach for Efficient Palm Reading

Suvajit Acharjee, Sirapop Nuannimnoi, Ching Yao Huang

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Palmistry or palm reading is the art of foretelling and characterizing persons through the study of palm lines and patterns. However, this field is still not much technically developed and a palmist has to analyze palms personally and manually. In this paper, we have proposed a deep learning approach to automatically detect patterns inside palm images. Our proposed automated palm reader can effectively detect and classify a user's palm according to our predefined labels.

    Original languageEnglish
    Title of host publicationProceedings - 25th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2020
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages171-174
    Number of pages4
    ISBN (Electronic)9781665403801
    DOIs
    StatePublished - Dec 2020
    Event25th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2020 - Taipei, Taiwan
    Duration: 3 Dec 20205 Dec 2020

    Publication series

    NameProceedings - 25th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2020

    Conference

    Conference25th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2020
    Country/TerritoryTaiwan
    CityTaipei
    Period3/12/205/12/20

    Keywords

    • Convolutional Neural Network
    • Deep Learning
    • Multi-label classification
    • Object detection
    • Palm reading
    • Palmistry

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