Identification of Chicken Eimeria Species from Microscopic Images by Using Convolutional Neural Network Method
Yükleniyor...
Dosyalar
Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Selçuk Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
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.
Açıklama
Anahtar Kelimeler
Convolutional Neural Nets, Deep learning, Disease Detection, Image Classification
Kaynak
Selcuk University Journal of Engineering Sciences
WoS Q Değeri
Scopus Q Değeri
Cilt
21
Sayı
02
Künye
Küçükkara, Z., Özkan, İ. A., Taşdemir, Ş., (2022). Identification of Chicken Eimeria Species from Microscopic Images by Using
Convolutional Neural Network Method. Selcuk University Journal of Engineering Sciences, 21, (02), 69-74.
