2nd IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET 2020)

26-27 August, 2020

Kota Kinabalu, Sabah

Introduction

The IEEE Sabah subsection is organizing the 2nd IEEE International Conference on Artificial Intelligence in Engineering and Technology 2020 (IICAIET2020), co-organized by the Artificial Intelligence Research Unit, Universiti Malaysia Sabah (UMS) and the Faculty of Robotics and Design, Osaka Institute of Technology (OIT), which will be held at Kota Kinabalu, Sabah, Malaysia from 26 to 27 August 2020.

Objective

The conference will provide an excellent platform for knowledge exchange between researchers working in the areas of Artificial Intelligence.

Organizer and Technical Sponsor

IEEE Sabah Subsection


Co-Organizers

  • Artificial Intelligence Research Unit (AiRU), Faculty of Engineering, UMS
  • Faculty of Robotics and Design, OIT

Our History : 2018 IICAIET

IICAIET Registration
Welcome Address by Assoc. Prof. Dr. Ismail Saad, Chairperson of IICAIET 2018
Keynote Speech by Prof. Kukjin Chun, Director of IEEE Region 10
Keynote Speech by Prof. Sigeru Omatu, Osaka Institute of Technology

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IICAIET 2018 Keynote Speaker 1 : Prof. Kukjin Chun , Director of IEEE Region 10

Title: Introduction to MEMS technology and IEEE

Abstract:

MEMS(Microelectromechanical Systems) technology is micrometer-scale devices that integrate electrical, mechanical, optical, biological, thermal and chemical elements. MEMS technology also provides fabrication platform for the realization of small structures in three-dimension on many different substrates and are usually fabricated by similar process to microelectronics, so they provide significant cost advantages when batch fabricated. They also have the advantages of monolithically integrated with Integrated Circuits for higher performance. In this talk, a camera-based distance sensor will be addressed as well as a few physical sensors based on MEMS technology. The sensor consists of conventional camera module with a tunable aperture for obtaining real-time image and range detection simultaneously. The tunable aperture uses light modulation characteristic of liquid crystal (LC) with 3V of operating voltage and 9.84ms of response time. Two images are captured by the camera and the sensor measures the distance by using two images with different depth-of-field to improve depth estimation accuracy. Especially, deep learning technique was applied to solve the DFD problem (Siamese and Resnet structure) with a synthetic experiment on the NYU-v2 dataset to verify the performance of the proposed model. The sensor has no mechanically movable parts, which ensures higher reliability and little spherical aberration. The cost of this sensor is much lower than conventional range sensor for vehicles such as Radio Detection And Ranging (radar) or Light Detection And Ranging (lidar). In the end of the talk, IEEE(Institute of Electrical and Electronics Engineers) will be introduced which holds over 420,000 membership and runs over 1,800 conferences every year along with the benefits for IEEE members.The tunable aperture uses light modulation characteristic of liquid crystal (LC) with 3V of operating voltage and 9.84ms of response time. Two images are captured by the camera and the sensor measures the distance by using two images with different depth-of-field to improve depth estimation accuracy. Especially, deep learning technique was applied to solve the DFD problem (Siamese and Resnet structure) with a synthetic experiment on the NYU-v2 dataset to verify the performance of the proposed model. The sensor has no mechanically movable parts, which ensures higher reliability and little spherical aberration. The cost of this sensor is much lower than conventional range sensor for vehicles such as Radio Detection And Ranging (radar) or Light Detection And Ranging (lidar). In the end of the talk, IEEE(Institute of Electrical and Electronics Engineers) will be introduced which holds over 420,000 membership and runs over 1,800 conferences every year along with the benefits for IEEE members.

IICAIET 2018 Keynote Speaker 2: Prof. Sigeru Omatu, Osaka Institute of Technology

Title: Feature Extraction from Spectral Images of Bills

Abstract:

There appear many faked bills according to the progress of printing technology. This paper considers a method to select the true bill or counterfeit bill by using image processing to use spectral band-data. We try to test using Singapore bills and show the procedure.

Biography :

Sigeru Omatu is Professor of at the Department of System Design Engineering, Faculty of Robotics & Design Engineering, Osaka Institute of Technology, Osaka, Japan. He received his Ph.D. in Electronic Engineering from Osaka Prefecture University in 1974 and joined the faculty at University of Tokushima in 1969. He was Professor of University of Tokushima in 1988 and Professor of Osaka Prefecture University in 1995. He has been Professor of Osaka Institute of Technology since 2010. His honors and awards include the Best Paper Awards for Distributed Parameter System Theory, IEE of Japan, 1991, for Intelligent Classification, JSME, 1995, for Coin and Bill Classification, SICE, Japan, 1995, for Intelligent Smell Classification, IARIA, 2008, for Neuro-Control, IARIA, 2009. Furthermore, he received Ichimura Distinguished Award for Intelligent Classification, New Technology Development Foundation, 1996, Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology, Science, Prizes for Science and Technology (Research Category), 2011. His research area covers intelligent signal processing, pattern recognition, intelligent control, and adaptive control.



Past Indexing

IICAIET 2018