Author

M. Koklu

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Open access Sep 2026

Automated classification of dental implant categories on panoramic radiographs using YOLOv8 and YOLO11 models

This study investigated the feasibility of automatically classifying panoramic radiographs into four dental implant categories using YOLOv8 and YOLO11 architectures. The proposed framework aims to support automated image-level implant category classification by providing rapid image analysis together with Grad-CAM visu...

E. Yasin, S. Sefati, Răzvan Crăciunescu et al. · Scientific Reports · 0 citations

Open access Oct 2026

Hybrid Deep Feature Extraction and Ensemble Machine Learning for Potato Leaf Disease Classification in Uncontrolled Field Conditions

Early and accurate diagnosis of potato leaf diseases is critical for preventing yield losses under real field conditions. This study proposes a hybrid deep feature–based machine learning framework that combines transfer learning and ensemble classifiers to automatically identify seven potato leaf disease classes from i...

Cihan Ünal, Cengizhan Tumer, E. Yasin et al. · Tarım Bilimleri Dergisi · 0 citations

Open access Aug 2026

Data-Driven Prediction of Processing Times and Delays Across Supply Chain Operational Stages Using Machine Learning

This study proposes an ensemble learning framework to predict personnel data entry durations across six operational stages using transaction records collected from an operational supply chain information system. To accurately represent operational performance, processing times were calculated in working minutes by excl...

Muhammed Yildiray Surmen, Oya Kılcı, Selime Sinem Bahar et al. · Intelligent Methods in Engin... · 0 citations

Open access Jul 2026

Automated classification of maxillary and mandibular dental views on intraoral photographs: a comparative benchmark study and mobile proof-of-concept.

This study benchmarks deep learning and machine learning approaches for classifying pediatric dental views using a publicly available dataset of 9,562 intraoral images from children aged 1-14 years, covering eight maxillary and mandibular view classes and highlights the potential of explainable, mobile-based AI systems...

E. Yasin, M. Koklu, Mohannad Alkanan et al. · BMC Oral Health · 0 citations