Browsing by Author "Isik, Sahin"

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    Potential of SEM and Deep Learning in Archaeobotanical Identification of Ancient Wheat Varieties
    (Routledge Journals, Taylor & Francis Ltd, 2025) Anagun, Yildiray; Isik, Sahin; Olgun, Murat; Ulker, Mehmet; Koyuncu, Onur; Dikmen, Gokhan; Biber, Hanifi
    This study investigated the morphological similarity between bread wheat landraces from the Van Lake Basin and ancient Urartian wheat seeds (9th century BCE) discovered at & Ccedil;avu & scedil;tepe Fortress, utilising a Convolutional Neural Network (CNN)-based framework. Scanning Electron Microscopy (SEM) datasets were created using 15 lines from 10 landraces and the ancient seeds; EfficientNetB0, ResNet18 and InceptionResNetV2 models were employed to extract discriminative surface texture features. The ancient wheat samples showed the highest surface-texture similarity to the Muradiye-1-1 line (Red Kirik wheat) across the tested models (39.8% to 44.1%). These results suggest a phenotypic convergence between ancient and modern landraces under similar agroecological conditions, demonstrating the utility of CNN models for archaeobotanical analysis.