Scopus
YÖKSİS Eşleşti
A CNN-SVM study based on selected deep features for grapevine leaves classification
Measurement: Journal of the International Measurement Confederation · Ocak 2022
YÖKSİS Kayıtları
A CNN-SVM Study Based on Selected Deep Features for Grapevine Leaves Classification
Measurement · 2022 SCI-Expanded
DOÇENT MURAT KÖKLÜ →
A CNN-SVM study based on selected deep features for grapevine leaves classification
Measurement · 2022 SCI-Expanded
DOÇENT İLKER ALİ ÖZKAN →
Makale Bilgileri
DergiMeasurement: Journal of the International Measurement Confederation
Yayın TarihiOcak 2022
Cilt / Sayfa188
Scopus ID2-s2.0-85119057932
Özet
The main product of grapevines is grapes that are consumed fresh or processed. In addition, grapevine leaves are harvested once a year as a by-product. The species of grapevine leaves are important in terms of price and taste. In this study, deep learning-based classification is conducted by using images of grapevine leaves. For this purpose, images of 500 vine leaves belonging to 5 species were taken with a special self-illuminating system. Later, this number was increased to 2500 with data augmentation methods. The classification was conducted with a state-of-art CNN model fine-tuned MobileNetv2. As the second approach, features were extracted from pre-trained MobileNetv2′s Logits layer and classification was made using various SVM kernels. As the third approach, 1000 features extracted from MobileNetv2′s Logits layer were selected by the Chi-Squares method and reduced to 250. Then, classification was made with various SVM kernels using the selected features. The most successful method was obtained by extracting features from the Logits layer and reducing the feature with the Chi-Squares method. The most successful SVM kernel was Cubic. The classification success of the system has been determined as 97.60%. It was observed that feature selection increased the classification success although the number of features used in classification decreased.
Yazarlar (5)
1
Murat Koklu
ORCID: 0000-0002-2737-2360
2
M. Fahri Unlersen
3
Ilker Ali Ozkan
4
M. Fatih Aslan
5
Kadir Sabanci
Anahtar Kelimeler
Deep learning
Grapevine leaves
Leaf identification
SVM
Transfer learning
Kurumlar
Karamanoğlu Mehmetbey Üniversitesi
Karaman Turkey
Necmettin Erbakan Üniversitesi
Meram Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
93
Atıf
5
Yazar
5
Anahtar Kelime