Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Hayder Ibrahim Hendi
University of Thi Qar
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Design a monitoring system for COVID-19 patients Hayder Ibrahim Hendi; Haider Hassan Mshali
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp304-309

Abstract

This paper considers to developing application software that can assist COVID-19 patients in-home quarantine to know their situations and call the emergence center when the patient needs it. It includes a smart band as well as an application on the smartphone, the smart band can determine blood oxygen levels, the temperature of the patient, environmental temperature and humidity, also daily activities that affect the decision to go to the hospital or stay at home. The core of the proposed project is using ontology and semantics web to process the data that coming from sensors (physiology and environment), and the information of patients stored in the database on the mobile application. The response depends on the dataset of affect sensors parameters and type of activity the patient at the time. There are three types of response to proposed program is (normal, alert, and emergency).
Realtime face matching and gender prediction based on deep learning Thongchai Surinwarangkoon; Vinh Truong Hoang; Ali Vafaei-Zadeh; Hayder Ibrahim Hendi; Kittikhun Meethongjan
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4068-4075

Abstract

Face analysis is an essential topic in computer vision that dealing with human faces for recognition or prediction tasks. The face is one of the easiest ways to distinguish the identity people. Face recognition is a type of personal identification system that employs a person’s personal traits to determine their identity. Human face recognition scheme generally consists of four steps, namely face detection, alignment, representation, and verification. In this paper, we propose to extract information from human face for several tasks based on recent advanced deep learning framework. The proposed approach outperforms the results in the state-of-the-art.
Co-Authors Ali Vafaei-Zadeh Haider Hassan Mshali Kittikhun Meethongjan Thongchai Surinwarangkoon Vinh Truong Hoang