The International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) is proud to announce the ICIIBMS 2017 Student Travel Award (ICIIBMS 2017 STA) provided by our technical co-sponsor, The IEEE Computer Society. The IEEE Computer Society will award up to five students a maximum of $600 USD each, to be applied toward airline travel for attendance to the ICIIBMS 2017 Conference.
We encourage all students to submit a high quality paper in order to be eligible to win the ICIIBMS 2017 STA.
Eligibility
The award winner must be a student who is a first author or co-author of a paper, and he/she must present the paper at the ICIIBMS 2017.
The paper must be of high quality, and written in a concise manner that describes state of the art research in his/her domain.
Travel Award Notification
The Student Travel Awards will be announced during the Conference closing ceremony. Therefore, to receive the STA, students must be present at the closing ceremony.
Documents and Reimbursement
Awardees will submit a reimbursement request form to the IEEE Computer Society, along with all receipts of airline tickets, and then the Computer Society will reimburse up to $600 USD.
After the conference awardees will be given instructions for submitting the necessary documents.
Optimal Feature Extraction and Feature Subsets for Various Machine Learning Algorithms Targeting Freezing of Gait Detection
Val Mikos
National University of Singapore
Unfortunately the student travel award is not available for ICIIBMS 2019
Autonomous Flight Drone for Infrastructure (transmission line) Inspection-3"
Michinari Morita
National Institute of Technology Okinawa College, Japan
November 25 - 27, 2021 - Oita, Japan
Developing a Simplified Maintenance & Rehabilitation Activity Prioritization Tool for Afghanistan Roads
NODRAT Fardeen
Graduate School of Engineering & Science, University of the Ryukyus Okinawa, Japan
Verification Experiment for Drone Charging Station Using RTK-GPS
Kyan Motoki
National Institute of Technology Okinawa College, Japan
Artificial Neural Network Based Nuclei Segmentation on Cytology Pleural Effusion Images
Khin Yadanar Win
Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang Bangkok, Thailand