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 languageAmerican English
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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