Evaluation of Deep Learning Models for Predicting the Support and Resistance Levels in Stock Market

JIITA, vol.6 no.3, p.586-599, 2022, DOI: 10.22664/ISITA.2021.6.3.586 T. Indhumathy1*), T. Velmurugan2*) 1) Research Scholar, PG and Research Department of Computer Science,D. G. Vaishnav College, Chennai-600106, Tamil Nadu, India2) Associate Professor, PG and Research Department of Computer Science, D. G. Vaishnav College, Chennai-600106, Tamil Nadu, India Abstract: Deep Learning evolved from Artificial Intelligence and has been […]

Development of HW/SW Platform for Real-Time Tests of Radar Front-End Module for Radar Machine Learning

JIITA, vol.6 no.3, p.600-609, 2022, DOI: 10.22664/ISITA.2021.6.3.600 YoungSeok Jin 1) , Eugin Hyun *2) 1) Division of Automotive Technology, DGIST, Daegu, Korea2) Division of Automotive Technology, DGIST, Daegu, Korea Abstract: In this paper, we developed a hardware and software platform of a real-time data logging system to verify radar front-end module (FEM) and signal-processing algorithms. […]

Real-time Face Presentation Attack Detection with a Single RGB camera

JIITA, vol.6 no.3, p.610-616, 2022, DOI: 10.22664/ISITA.2021.6.3.610 Myoung-Kyu Sohn 1,*), Hyunduk Kim 1) 1) Division of Automotive Technology, DGIST, Daegu, Republic of Korea Abstract: As face recognition technology has become more common, image-based face authentification systems are being widely used. At the same time, techniques for hacking these technologies have begun to appear. Face spoofing, […]

Electric kickboard safety regulation violation checking system using image classifier

JIITA, vol.6 no.3, p.579-585, 2022, DOI:10.22664/ISITA.2021.6.3.579 SeongU Yun 1), Sehui Yoo 2) and Yoosoo Oh 3,*) 1) 2) 3) Dept. of ICT Convergence, Dept. of AI, Daegu University, Gyeongsan-si, Republic of Korea Abstract: As the safety accidents of electric scooters have been increasing, the electric kickboard-related legislation was revised in 2020. The revised road traffic […]

Scroll to top