Scopus
YÖKSİS DOI Eşleşti
SJR Q1
Classification of bread wheat varieties with a combination of deep learning approach
European Food Research and Technology · Ocak 2024
YÖKSİS Kayıtları
Classification of bread wheat varieties with a combination of deep learning approach
Springer Science and Business Media LLC · 2024 SCI-Expanded
Doç. Dr. ADEM GÖLCÜK →
Classification of bread wheat varieties with a combination of deep learning approach
European Food Research and Technology · 2024 SCI-Expanded
Doç. Dr. ALİ YAŞAR →
YÖKSİS Kayıtları — ISSN Eşleşmesi
The effect of nitrogen fertilization on tocopherols in rapeseed genotypes
2008 ISSN: 1438-2377 SCI-Expanded
Dr. Öğr. Üyesi İRFAN ÖZER →
The effect of nitrogen fertilization on tocopherols in rapeseed genotypes
2008 ISSN: 1438-2377 SCI-Expanded 14 atıf
Dr. Öğr. Üyesi İRFAN ÖZER →
The effect of various types of poultry pre and post rigor meats on emulsification capacity water holding capacity and cooking loss
2005 ISSN: 1438-2377 SSCI 15 atıf
Prof. Dr. CEMALETTİN SARIÇOBAN →
The effect of irrigation and harvest time on bioactive properties of olive fruits issued from some olive varieties grown in Mediterranean region
2020 ISSN: 1438-2377 SCI
Doç. Dr. NURHAN USLU →
The effect of irrigation and harvest time on bioactive properties
of olive fruits issued from some olive varieties grown in Mediterranean
region
2020 ISSN: 1438-2377 SCI-Expanded
Prof. Dr. MEHMET MUSA ÖZCAN →
Volatile profile evolution and sensory evaluation of traditional skinbag Tulum cheeses manufactured in Karaman mountainous region of Turkey during ripening
2021 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. TALHA DEMİRCİ →
Computer Vision Classification of Dry Beans (Phaseolus Vulgaris L.) Based on Deep Transfer Learning Techniques
2022 ISSN: 1438-2377 SCI-Expanded Q2
Arş. Gör. MUSA DOĞAN →
The influence of decoction and infusion methods and times on antioxidant activity, caffeine content and phenolic compounds of coffee brews
2022 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. NURHAN USLU →
A New Hybrid Model for Classification of Corn Using Morphological Properties
2023 ISSN: 1438-2377 SCI-Expanded Q2
Prof. Dr. ŞAKİR TAŞDEMİR →
The effect of nitrogen fertilization on tocopherols in rapeseed genotypes
2008 ISSN: 1438-2377 SCI-Expanded Q2
Dr. Öğr. Üyesi İRFAN ÖZER →
A review: benefit and bioactive properties of olive (Olea europaea L.) leaves
2016 ISSN: 1438-2377 SCI-Expanded
Prof. Dr. MEHMET MUSA ÖZCAN →
Computer vision classification of dry beans (Phaseolus vulgaris L.) based on deep transfer learning techniques
2022 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. İLKER ALİ ÖZKAN →
Classification of Cicer arietinum varieties using MobileNetV2 and LSTM
2023 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. ADEM GÖLCÜK →
Benchmarking analysis of CNN models for bread wheat varieties
2023 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. ALİ YAŞAR →
Classification of Deep Image Features of Lentil Varieties with Machine Learning Techniques
2023 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. MURAT KÖKLÜ →
A New Hybrid Model for Classification of Corn Using Morphological Properties
2023 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. MURAT KÖKLÜ →
Detection of fish freshness using artificial intelligence methods
2023 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. MURAT KÖKLÜ →
Segmentation of dry bean (Phaseolus vulgaris L.) leaf disease images with U-Net and classification using deep learning algorithms
2023 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. MURAT KÖKLÜ →
Classification of Cicer arietinum varieties using MobileNetV2 and LSTM
2023 ISSN: 1438-2377 SCI-Expanded Q2
Doç. Dr. ALİ YAŞAR →
Makale Bilgileri
ISSN14382377
Yayın TarihiOcak 2024
Cilt / Sayfa250 · 181-189
Scopus ID2-s2.0-85174178746
Özet
Wheat is one of the most produced and consumed grain products worldwide. Wheat is the main grain product in developed and underdeveloped countries. Flour obtained from wheat is used in the production of bread, the most basic food product, and in the production of cakes used to celebrate the most special days. Therefore, knowing the pure bread wheat varieties is important both for production and for those who use wheat as flour. However, since wheat varieties are very similar to each other, it is difficult to distinguish them. To solve this problem, a pre-trained hybrid model based on convolutional neural network (CNN) is proposed in this study to classify bread wheat varieties. Images of five different registered bread wheat varieties were captured and a bread wheat image data set was created by separating them with image processing techniques to be used in deep learning. Then, the obtained images were classified using transfer learning with fine-tuning on the Xception model, one of the pre-trained CNN models. To increase the classification success, Xception CNN model and BiLSTM (Bidirectional Long Short-Term Memory) algorithms hybrid (Xception + BiLSTM) models were obtained. As a result of classifications, the highest classification success was obtained from the Xception + BiLSTM model with 97.73%. The results revealed that the proposed methods can be used in systems used for classification of bread wheat varieties and to obtain pure wheat varieties automatically.
Yazarlar (3)
1
Ali Yasar
2
Adem Golcuk
ORCID: 0000-0002-6734-5906
3
Omer Faruk Sari
Anahtar Kelimeler
BiLSTM
CNN
Hybrid
LSTM
Wheat classification
Xception
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
University of Portsmouth
Portsmouth United Kingdom
Scimago Dergi (ISSN Eşleşmesi)
European Food Research and Technology
Q1
SJR Skoru0,744
H-Index131
YayıncıSpringer Science and Business Media Deutschland GmbH
ÜlkeGermany
Food Science (Q1)
Industrial and Manufacturing Engineering (Q1)
Biochemistry (Q2)
Biotechnology (Q2)
Chemistry (miscellaneous) (Q2)
Metrikler
19
Atıf
3
Yazar
6
Anahtar Kelime