"Machine Learning Approach for Classifying College Scholastic Ability Test ..."

Jung-Gu Choi et al. (2022)

> Home

Details and statistics

DOI: 10.1109/ACCESS.2022.3173629

access: open

type: Journal Article

metadata version: 2025-03-03

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/access/ChoiKNKPCCH22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/access/ChoiKNKPCCH22
Jung-Gu Choi, Inhwan Ko, Yoonjin Nah, Bora Kim, Yongwan Park, Jihyun Cha, Jongkwan Choi, Sanghoon Han:
Machine Learning Approach for Classifying College Scholastic Ability Test Levels With Unsupervised Features From Prefrontal Functional Near-Infrared Spectroscopy Signals. IEEE Access 10: 50864-50877 (2022)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.