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ORCIDÖzlem Albayrak
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2020 – today
- 2024
[j3]Bilgin Umut Deveci
, Mert Celtikoglu, Özlem Albayrak, Perin Ünal, Pinar Kirci:
Transfer Learning Enabled Bearing Fault Detection Methods Based on Image Representations of Single-Dimensional Signals. Inf. Syst. Frontiers 26(4): 1345-1397 (2024)- [c15]Inci Sila Kaleli, Perin Ünal, Bilgin Umut Deveci, Özlem Albayrak, Ahmet Murat Özbayoglu:
A Domain-Aware Federated Learning Study for CNC Tool Wear Estimation. MobiWIS 2024: 250-265 - 2023
- [c14]Abdüsselam Koç, Özlem Albayrak, Yasar Kurt, Perin Ünal:
A Study to Compare YOLO Family Models for Metal Surface Anomaly Detection. IEEE Big Data 2023: 5835-5841 - 2022
- [c13]Seyithan Temel, Emre Ummak, Abdülkadir Tokgöz, Furkan Isik, Özlem Albayrak, Perin Ünal, A. Murat Özbayoglu:
Control System Design and Implementation Based on Big Data and Ontology. IEEE Big Data 2022: 6048-6056 - [c12]Perin Ünal, Özlem Albayrak, Meerim Kubatova, Bilgin Umut Deveci, Ege Çirakman, Ç. Ipek Koçal, A. Murat Özbayoglu:
A Big Data Application in Manufacturing Industry-Computer Vision to Detect Defects on Bearings. IEEE Big Data 2022: 6074-6083 - [c11]Bilgin Umut Deveci, Hilal Bas, Emre Ummak, Özlem Albayrak, Perin Ünal:
A Thorough Analysis and Comparison of Data Communication Protocols Used in Industry 4.0: the Case of Smart-CNC. FiCloud 2022: 199-206 - [c10]Fatih Yalliç, Özlem Albayrak, Perin Ünal:
Asset Administration Shell Generation and Usage for Digital Twins: A Case Study for Non-destructive Testing. IN4PL 2022: 299-306 - [p2]Perin Ünal, Özlem Albayrak, Moez Jomâa, Arne J. Berre:
Data-Driven Artificial Intelligence and Predictive Analytics for the Maintenance of Industrial Machinery with Hybrid and Cognitive Digital Twins. Technologies and Applications for Big Data Value 2022: 299-319 - 2021
- [j2]Sahan Yoruç Selçuk, Perin Ünal, Özlem Albayrak, Moez Jomâa:
A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data. Inf. 12(10): 386 (2021) - [c9]Aras Firat Unal, Ali Yuce Kaleli, Emre Ummak, Özlem Albayrak:
A Comparison of State-of-the-Art Machine Learning Algorithms on Fault Indication and Remaining Useful Life Determination by Telemetry Data. FiCloud 2021: 79-85 - [c8]Bilgin Umut Deveci, Mert Celtikoglu, Tilbe Alp, Özlem Albayrak, Perin Ünal, Pinar Kirci:
A Comparison of Deep Transfer Learning Methods on Bearing Fault Detection. FiCloud 2021: 285-292 - [c7]Baris Güney Özdilli, Mustafa Bora Arslan, Tilbe Alp, Özlem Albayrak, Perin Ünal, Özlem Bozkurt, A. Murat Özbayoglu:
Performance Analysis of Machine Learning Models for Object Recognition in Underwater Video Images. SIU 2021: 1-4
2010 – 2019
- 2015
- [c6]Özlem Albayrak:
Instructor's Acceptance of Games Utilization in Undergraduate Software Engineering Education: A Pilot Study in Turkey. GAS@ICSE 2015: 43-49 - 2014
- [j1]Özlem Albayrak, Jeffrey C. Carver:
Investigation of individual factors impacting the effectiveness of requirements inspections: a replicated experiment. Empir. Softw. Eng. 19(1): 241-266 (2014) - [c5]Özlem Albayrak:
UML Diyagramları Kullanımının Yazılım Gerekleri Gözden Geçirme Performansına Etkileri: Bir Replikasyon Çalışması. UYMS 2014 - [p1]Baris Özkan, Özlem Albayrak, Onur Demirörs:
Software Quality and Model-Based Process Improvement. Computing Handbook, 3rd ed. (1) 2014: 79: 1-27 - 2010
- [c4]Özlem Albayrak, David Davenport:
Impact of maintainability defects on code inspections. ESEM 2010
2000 – 2009
- 2009
- [c3]Özlem Albayrak, Hülya Kurtoglu, Mert Biçakçi:
Incomplete Software Requirements and Assumptions Made by Software Engineers. APSEC 2009: 333-339 - [c2]Özlem Albayrak:
An experiment to observe the impact of UML diagrams on the effectiveness of software requirements inspections. ESEM 2009: 506-510 - [c1]Alok Mishra, Deepti Mishra, Özlem Albayrak:
ISDE 2009 PC Co-chairs' Message. OTM Workshops 2009: 226-227
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last updated on 2024-10-07 22:22 CEST by the dblp team
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