Article Per Year (5 Year)
p-Index From 2021 - 2026
0.835
P-Index
This Author published in this journals
All Journal The Indonesian Journal of Computer Science
Foteini Filippidou
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering Engineering

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

Found 2 Documents
Search

 1 
Anti-spoofing methods in face recognition Bezas, Konstantinos; Foteini Filippidou
The Indonesian Journal of Computer Science Vol. 12 No. 3 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i3.3198

Abstract

Biometric data are personal data that result from specialized processing techniques and are associated with physical, biological, or behavioral characteristics of a natural person that allow for or confirm their unquestionable identification. These characteristics or identifiers are permanent and unique. This paper refers to the biometric characteristics used by systems, their mode of operation, and the categories they are distinguished in. The types of attacks that they may be subjected to are then analyzed, along with the anti-spoofing methods proposed in some studies specifically for systems that use the face as a biometric feature. Finally, numerical data is presented regarding the scientific interest that the topic of anti-spoofing methods in biometric systems has shown in the last decade.
The Role of Artificial Intelligence and Machine Learning in Smart and Precision Agriculture Bezas, Konstantinos; Foteini Filippidou
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3278

Abstract

In recent years, the agricultural sector has been undergoing a new "green revolution" characterized by the increasing use of information and communication technology (ICT) and the transition from traditional farming methods to smart agricultural practices, also known as Agriculture 4.0. Robotics, combined with the use of drones, the emerging field of the Internet of Things (IoT), machine learning, and artificial intelligence, are now being deployed in digital transformation services in agriculture, aiming to optimize crop performance and agricultural sustainability. According to research and international literature, the new trends are now oriented towards the development of global and state-of-the-art connected agricultural systems through digital management platforms, with the goal of facilitating the flow of data and information. Although many efforts are being made to implement smart agriculture, there are still challenges that require further research.
Co-Authors Bezas, Konstantinos Konstantinos Bezas