Scopus
Identification of Sheep Breeds by CNN- Based Pre-Trained Inceptionv3 Model
2022 11th Mediterranean Conference on Embedded Computing, MECO 2022 · Ocak 2022
Makale Bilgileri
Dergi2022 11th Mediterranean Conference on Embedded Computing, MECO 2022
Yayın TarihiOcak 2022
Scopus ID2-s2.0-85133960804
Özet
It is very important for the farmers who produce sheep to know which sheep breeds are in the sheep herd and which breeds can provide more income than others in order to better manage their resources. For this purpose, we propose a CNN-based model that can detect the breed of sheep from facial images to detect sheep breeds quickly, effectively, and at a low cost. In this study, a dataset containing a total of 1680 images belonging to 4 different sheep breeds was used. The 2048 deep features of each of these images were extracted using the InceptionV3 CNN model and given as inputs to the kNN, SVM, and ANN classifiers. As a result of the classification processes, the highest accuracy in the classification of sheep breeds was obtained as 92.3% from the ANN model. When the results of the study are evaluated, it is possible to say that success has been achieved in the classification of sheep breeds with this study.
Yazarlar (4)
1
Murat Koklu
ORCID: 0000-0002-2737-2360
2
Ilkay Cinar
ORCID: 0000-0003-0611-3316
3
Yavuz Selim Taspinar
ORCID: 0000-0002-7278-4241
4
Ramazan Kursun
ORCID: 0000-0002-6729-1055
Anahtar Kelimeler
Classification
deep features
deep learning
sheep breed dataset
transfer learning
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
10
Atıf
4
Yazar
5
Anahtar Kelime