Determination of the Live Weight of Farm Animals with Deep Learning and Semantic Segmentation Techniques
Applied Sciences (Switzerland), cilt.13, sa.12, 2023 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 13 Sayı: 12
- Basım Tarihi: 2023
- Doi Numarası: 10.3390/app13126944
- Dergi Adı: Applied Sciences (Switzerland)
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
- Anahtar Kelimeler: animal weight estimation, deep learning, image processing, semantic segmentation, stereo vision
- Maltepe Üniversitesi Adresli: Evet
Özet
In cattle breeding, regularly taking the animals to the scale and recording their weight is important for both the performance of the enterprise and the health of the animals. This process, which must be carried out in businesses, is a difficult task. For this reason, it is often not performed regularly or not performed at all. In this study, we attempted to estimate the weights of cattle by using stereo vision and semantic segmentation methods used in the field of computer vision together. Images of 85 animals were taken from different angles with a stereo setup consisting of two identical cameras. The distances of the animals to the camera plane were calculated by stereo distance calculation, and the areas covered by the animals in the images were determined by semantic segmentation methods. Then, using all these data, different artificial neural network models were trained. As a result of the study, it was revealed that when stereo vision and semantic segmentation methods are used together, live animal weights can be predicted successfully.