TEEP@AsiaPlus Grant Penelitian di National Chung Cheng University, Taiwan didapat oleh Nova Eka Budiyanta dan Gregorius Airlangga Dosen Teknik Elektro dan Sistem Informasi UAJ

09/01/2018 00:00:00

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Two lecturers from Atma Jaya Catholic University of Indonesia, Mr. Nova Eka Budiyanta, M. Pd from the Electrical Engineering study program and Mr. Gregorius Airlangga, M. T from the information system study program fulfilling the invitation for research visiting within 3 months at National Chung Cheng University (CCU), Taiwan. This program is to enhance the collaboration between the College of Engineering (CoE) of National Chung Cheng University (CCU) and the Faculty of Engineering of Atma Jaya Catholic University of Indonesia. The aim of this activity is that the researcher on both sides can do some research project together. In this activity, They joined Applied Computing and Multimedia Laboratory (ACM Lab) supervised by Prof. Ching Chun Huang with the project title "Applying machine learning approach to image processing and computer vision". ACM laboratory focuses on researching Deep Learning, Machine Learning, Computer Vision, Image Processing and applying them to some applications: Fusion-based Applications, Multi-Camera Fusion and Cooperation Sensors Algorithms for Scene Understanding, Delivery robot design (ie: SLAM), Computational Camera, Imaging, Photography, the Synthesis of Stereoscopic Images for 3D Display. Their current projects are strongly relative to deep learning and machine learning such as Parking Space Detection, Autonomous Vehicle, Delivery Robot Design, Sensor Fusion Applications, and Museum Guidance System. "Because of the many overlapping research projects, I hope we can establish more research cooperation for the future", said Mr. Nova Eka Budiyanta. Responding to Mr. Nova‘s statement, Mr. Gregorius Airlangga added, "This is a real action and a good example to establish international cooperation and implement a research culture in the academic environment of Atma Jaya Catholic University of Indonesia."

 

 In Dept. of Electrical Engineering of CCU, Mr. Nova Eka Budiyanta handled research on the vision system and control of the Robot Arm. The purpose of this study is the creation of a control algorithm on the Robot Arm that makes the Robot Arm can understand human intentions and can collaborate to help humans complete a task. This research has started due to his interest in the movement of the industrial world that now increasingly rapid and competing towards industry 4.0. One characteristic of Industry 4.0 is the creation of an automation system in every line. One way to take part in this automation system is to use Robotic Arm Manipulators to help human work in the industry. Mr. Nova Eka Budiyanta uses Robot Arm produced by one of robot company in Taiwan to implement his algorithm. The Robot Arm can move using 6 Degree of Freedom (DOF) and can be controlled with the industry‘s default operating system or also with an open source operating system called ROS. There are several advantages of the Robot Arm, one of them is equipped with industrial vision / “Eye-in-Hand” camera standard that can be used to capture the image so that Mr. Nova Eka Budiyanta can apply intelligence and algorithm to the Robot Arm to be able to make decisions based on the image captured by the camera from the Robot Arm.

 On the other hand, Mr. Gregorius Airlangga handle medical image segmentation system research. This project has been started due to his interest to make automatic medical image segmentation so computer could segment region of interest in medical image automatically and could help radiologist work easily and quickly. his work only focus on developing robust medical image segmentation system for knowledge acquisition. At the end of the month, he successfully design an initial system to do data acquisition in medical image processing. The system could work in website environment and allowing the radiologist, doctor and medical image processing researcher to collect data together. After that the collected data will be entered into into machine learning  algorithm to make a model to predict medical image location. For the future direction, he would like to analyze data every three months and extract the knowledge into his algorithm model to make a more robust automatic medical image segmentation system.