Identification of Chicken Eimeria Species from Microscopic Images by Using Convolutional Neural Network Method
Yazarlar (3)
Zeki Küçükkara
Doç. Dr. İlker Ali Özkan Selçuk Üniversitesi, Türkiye
Prof. Dr. Şakir TAŞDEMİR Selçuk Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(Diğer hakemli uluslarası dergilerde yayınlanan tam makale)
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| Dergi Adı | Selcuk University Journal of Engineering Sciences | ||
| Dergi ISSN | 2757-8828 | ||
| Dergi Tarandığı Indeksler | Index Copernicus | ||
| Makale Dili | İngilizce | Basım Tarihi | 08-2022 |
| Cilt / Sayı / Sayfa | 21 / 2 / 69–74 | DOI | – |
| Makale Linki | https://sujes.selcuk.edu.tr/sujes/article/view/603 | ||
| UAK Araştırma Alanları |
Yapay Zeka
Görüntü İşleme
Gömülü Sistemler
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| Özet |
| Eimeria is a parasite that lives in the intestinal, bile duct, and liver tissues of various domestic animals such as rabbits, chickens, geese, ducks, cattle, pigs, cats, and dogs. Due to these conditions, these parasites can spread rapidly, negatively affect animal productivity, and lead to deadly results. For this reason, it is vital to determine the disease early and prevent its spread at an early age. Because of these parasites’ diversity, complexity, and similarity, a system automatically analyzes them using microscopic images is needed. A model was developed to address this problem using Convolutional Neural Networks to predict seven different types of noise on microscopic images. In the developed methodology, the average accuracy rate was 93.85%. This model developed to detect seven different types of parasites has shown that it can be used successfully. |
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