Items where Author is "Farea, Shawqi Mohammed Othman"

Article

Farea, Shawqi Mohammed Othman and Javidrad, Hamidreza and Ünel, Mustafa and Koç, Bahattin (2025) In-situ defect detection in directed energy deposition using thermal imaging and machine learning. Progress in Additive Manufacturing . ISSN 2363-9512 (Print) 2363-9520 (Online) Published Online First https://dx.doi.org/10.1007/s40964-025-01362-4

Farea, Shawqi Mohammed Othman and Mumcuoğlu, Mehmet Emin and Ünel, Mustafa (2025) An Explainable AI approach for detecting failures in air pressure systems. Engineering Failure Analysis, 173 . ISSN 1350-6307 (Print) 1873-1961 (Online)

Mumcuoğlu, Mehmet Emin and Farea, Shawqi Mohammed Othman and Ünel, Mustafa and Mise, Serdar and Unsal, Simge and Cevik, Enes and Yilmaz, Metin and Koprubasi, Kerem (2024) Detecting APS failures using LSTM-AE and anomaly transformer enhanced with human expert analysis. Engineering Failure Analysis, 165 . ISSN 1350-6307 (Print) 1873-1961 (Online)

Akay, Rustu and Saleh, Radhwan A. A. and Farea, Shawqi Mohammed Othman and Kanaan, Muzaffer (2022) Multilevel thresholding segmentation of color plant disease images using metaheuristic optimization algorithms. Neural Computing and Applications (SI), 34 (2). pp. 1161-1179. ISSN 0941-0643 (Print) 1433-3058 (Online)

Papers in Conference Proceedings

Ayyıldızlı, Ahmet Berke and Balota, Beyza and Tatari, Kerem and Farea, Shawqi Mohammed Othman and Ünel, Mustafa (2025) Anomaly detection in directed energy deposition: a comparative study of supervised and unsupervised machine learning algorithms. In: 22nd International Conference on Informatics in Control, Automation and Robotics (ICINCO 2025), Marbella, Spain

Özdek, Ufuk İsmail and Tonkaz, Yiğit Kaan and Farea, Shawqi Mohammed Othman and Ünel, Mustafa (2025) Semi-supervised anomaly detection in directed energy deposition using thermal images. In: 22nd International Conference on Informatics in Control, Automation and Robotics (ICINCO 2025), Marbella, Spain

Farea, Shawqi Mohammed Othman and Ünel, Mustafa and Koç, Bahattin (2024) Defect prediction in directed energy deposition using an ensemble of clustering models. In: 22nd IEEE International Conference on Industrial Informatics (INDIN), Beijing, China

Farea, Shawqi Mohammed Othman and Mumcuoğlu, Mehmet Emin and Ünel, Mustafa and Mise, Serdar and Ünsal, Simge and Çevik, Enes and Yılmaz, Metin and Köprübaşı, Kerem (2024) Prediction of failures in air pressure system: a semi-supervised framework based on transformers. In: 22nd IEEE International Conference on Industrial Informatics (INDIN), Beijing, China

Mumcuoğlu, Mehmet Emin and Farea, Shawqi Mohammed Othman and Ünel, Mustafa and Mise, Serdar and Unsal, Simge and Cevik, Enes and Yilmaz, Metin and Koprubasi, Kerem (2024) Air pressure system failures detection using LSTM-autoencoder. In: IEEE International Workshop on Metrology for Automotive (MetroAutomotive), Bologna, Italy

Saleh, Radhwan A. A. and Farea, Shawqi Mohammed Othman and Al-Huda, Zaid and Ertunc, Metin and Kvak, Daniel and Al-antari, Mugahed A. (2023) FXAI: fusing XAI for predicting COVID-19 using diverse chest x - ray images. In: 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), Fuzhou, China

Mumcuoğlu, Mehmet Emin and Farea, Shawqi Mohammed Othman and Ünel, Mustafa and Mise, Serdar and Unsal, Simge and Yilmaz, Metin and Koprubasi, Kerem (2023) Fuel consumption classification for heavy-duty vehicles: a novel approach to identifying driver behavior and system anomalies. In: AEIT International Conference on Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2023, Modena

Farea, Shawqi Mohammed Othman and Mumcuoğlu, Mehmet Emin and Ünel, Mustafa and Mise, Serdar and Unsal, Simge and Yilmaz, Metin and Köprübaşı, Kerem (2023) Towards driving-independent prediction of fuel consumption in heavy-duty trucks. In: AEIT International Conference on Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2023, Modena

Thesis

Farea, Shawqi Mohammed Othman (2025) Developing Data-Driven Models For Anomaly Detection In Automotive And Additive Manufacturing Applications. [Thesis]