Chestnut(Castanea sativa)Varieties Classification with Harris Hawks Optimization Based Selected Features and SVM
Yazarlar (3)
Arş. Gör. Mustafa Yurdakul Kirikkale Üniversitesi, Türkiye
Dr. Öğr. Üyesi İrfan Atabaş Kirikkale Üniversitesi, Türkiye
Prof. Dr. Şakir TAŞDEMİR Sinop Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.1109/iCACCESS61735.2024.10499473 | ||
| Kongre Adı | 2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS) | ||
| Kongre Tarihi | 08-03-2024 / 09-03-2024 | ||
| Basıldığı Ülke | Basıldığı Şehir | ||
| Bildiri Linki | https://ieeexplore.ieee.org/xpl/conhome/10499437/proceeding | ||
| UAK Araştırma Alanları |
Yapay Zeka
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| Özet |
| Chestnut(Castanea sativa) is a nutritious food with a hard outer shell. It is also used in different sectors for various purposes. Chestnut is a commercial product that is in demand worldwide due to its multi-purpose use. In order to determine the market value of chestnuts, it is necessary to classify it according to its types. With classical methods, people classify it manually. However, this method is tiring and error prone. In this study, for classifying chestnut varieties, features were extracted from chestnut images using various feature extraction methods. The extracted features were combined and classified with Linear, Poly and Radial Basis Function(RBF) kernels of Support Vector Machine(SVM). The combined handcrafted features and RBF kernel achieved an accuracy of 94.28%, precision of 93.83%, recall of 93.98%, F1-Score of 93.84%, and AUC of 99.25%. Furthermore, the most relevant features were selected using … |
| Anahtar Kelimeler |
| Arithmetic Optimization | Chestnut | Classification | Harris Hawks Optimization | Sooty Tern Optimization |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 2 |
| Google Scholar | 5 |