Deep Learning Assisted Intelligent Human Computer Interaction for Next Generation Internet Applications

Authors

  • Hasan Al Mehedi
  • Yong Seok Hwang
  • Jungpil Shin School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan

DOI:

https://doi.org/10.31449/inf.v48i2.6286

Abstract

Guest Editorial Preface

Author Biography

Jungpil Shin, School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan

Dr. Jungpil Shin is a professor of School of Computer Science and Engineering, The University of AIZU and Supervisor of Pattern Processing Lab, The University of AIZU. He is serving to the University of AIZU as an academician since 1999. His current research interests are pattern recognition, HCI (Human Computer Interaction), image processing, computer vision, and medical diagnosis. He is currently doing research on developing algorithms and systems for non-Touch input interfaces to recognize and identify the Human and Gesture, Non-touch character input system based on hand tapping gestures, Gesture based non-touch flick character input system, automatic diagnosis and clinical evaluation of neurological movement disorders disease, lung disease prediction and diagnosis using advanced image processing and machine intelligence techniques.

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Published

2024-05-28

How to Cite

Al Mehedi, H., Seok Hwang, Y., & Shin, J. (2024). Deep Learning Assisted Intelligent Human Computer Interaction for Next Generation Internet Applications. Informatica, 48(2). https://doi.org/10.31449/inf.v48i2.6286

Issue

Vol. 48 No. 2 (2024)

Section

Special Issue: Deep Learning Assisted Intelligent Human Computer Interaction for Next Generation Internet Applications

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