Sezen, Arda

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/6766
Name Variants
A., Sezen
A.,Sezen
Sezen,A.
S.,Arda
S., Arda
Arda Sezen
Sezen,Arda
Sezen, Arda
Arda, Sezen
Job Title
Yardımcı Doçent
Email Address
arda.sezen@atilim.edu.tr
Main Affiliation
Computer Engineering
Status
Website
ORCID ID
0000-0002-7615-3623
Scopus Author ID
57271674300
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
1
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
0
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
Scopus data could not be loaded because of an error. Please refresh the page or try again later.
This researcher does not have a WoS ID.
Scholarly Output

12

Articles

6

Views / Downloads

32/54

Supervised MSc Theses

4

Supervised PhD Theses

1

WoS Citation Count

7

Scopus Citation Count

40

Patents

0

Projects

1

WoS Citations per Publication

0.58

Scopus Citations per Publication

3.33

Open Access Source

5

Supervised Theses

5

JournalCount
International Journal of Computational and Experimental Science and Engineering3
8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 -- 8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 -- 21 September 2024 through 22 September 2024 -- Malatya -- 2034231
Bilişim Teknolojileri Dergisi1
Evolutionary Intelligence1
IEEE Access1
Current Page: 1 / 1

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

20241
Reset filters

Settings

Author: Türkmen, Güzin

Scholarly Output Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    Article
    Citation - Scopus: 22
    Comparative Analysis of Programming Languages Utilized in Artificial Intelligence Applications: Features, Performance, and Suitability
    (Prof.Dr. İskender AKKURT, 2024) Sezen, Arda; Türkmen, Güzin; Şengül, Gökhan
    This study presents a detailed comparative analysis of the foremost programming languages employed in Artificial Intelligence (AI) applications: Python, R, Java, and Julia. These languages are analysed for their performance, features, ease of use, scalability, library support, and their applicability to various AI tasks such as machine learning, data analysis, and scientific computing. Each language is evaluated based on syntax and readability, execution speed, library ecosystem, and integration with external tools. The analysis incorporates a use case of code writing for a linear regression task. The aim of this research is to guide AI practitioners, researchers, and developers in choosing the most appropriate programming language for their specific needs, optimizing both the development process and the performance of AI applications. The findings also highlight the ongoing evolution and community support for these languages, influencing long-term sustainability and adaptability in the rapidly advancing field of AI. This comparative assessment contributes to a deeper understanding of how programming languages can enhance or constrain the development and implementation of AI technologies.