Scopus
YÖKSİS Eşleşti
A new hybrid model for classification of corn using morphological properties
European Food Research and Technology · Mart 2023
YÖKSİS Kayıtları
A New Hybrid Model for Classification of Corn Using Morphological Properties
European Food Research and Technology · 2023 SCI-Expanded
PROFESÖR ŞAKİR TAŞDEMİR →
A New Hybrid Model for Classification of Corn Using Morphological Properties
European Food Research and Technology · 2023 SCI-Expanded
DOÇENT MURAT KÖKLÜ →
Makale Bilgileri
DergiEuropean Food Research and Technology
Yayın TarihiMart 2023
Cilt / Sayfa249 · 835-847
Scopus ID2-s2.0-85143224130
Özet
Automated classification of corn is important for corn sorting in intelligent agriculture. Corn classification process is a necessary and accurate process in many places in the world today. Correct corn classification is important to identify product quality and to distinguish good from bad. In this study, a hybrid model was proposed to classify the 3 corn species belonging to the Zea mays family. In the hybrid model, 12 different morphological features of corn were obtained. These morphological features were used for the classification process in the hybrid model created using machine learning (ML) algorithms. When morphological features were given as input to ML algorithms for normal classification, the test score was 96.66% for Decision Tree (DT), 97.32% for Random Forest (RF) and 96.66% for Naive Bayes (NB). With the proposed hybrid model, this rate has reached 100% test score in all three algorithms. Test processes were measured by statistical models. While Accuracy was 97.67% as a result of normal classification, this rate was 100% in hybrid model. The experimental results demonstrated the effectiveness of the proposed corn classification system.
Yazarlar (3)
1
Emre Avuçlu
2
Şakir Taşdemir
3
Murat Koklu
ORCID: 0000-0002-2737-2360
Anahtar Kelimeler
Computer vision
Corn classification
Image collection system
Machine learning
Kurumlar
Aksaray Üniversitesi
Aksaray Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
3
Atıf
3
Yazar
4
Anahtar Kelime