| Autor: |
Ghosh, Pritam, Mustafi, Subhranil, Mandal, Satyendra |
| Zdroj: |
International Journal of Computer Vision and Image Processing (IJCVIP); October 2020, Vol. 10 Issue: 4 p74-96, 23p |
| Abstrakt: |
In this paper an attempt has been made to identify six different goat breeds from pure breed goat images. The images of goat breeds have been captured from different organized registered goat farms in India, and almost two thousand digital images of individual goats were captured in restricted (to get similar image background) and unrestricted (natural) environments without imposing stress to animals. A pre-trained deep learning-based object detection model called Faster R-CNN has been fine-tuned by using transfer-learning on the acquired images for automatic classification and localization of goat breeds. This fine-tuned model is able to locate the goat (localize) and classify (identify) its breed in the image. The Pascal VOC object detection evaluation metrics have been used to evaluate this model. Finally, comparison has been made with prediction accuracies of different technologies used for different animal breed identification. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
|
