TY  - JOUR
TI  - Determining the Location of Tibial Fracture of Dog and Cat Using Hybridized Mask R-CNN Architecture
AB  - The aim of this study is to hybridize the original backbone structure used in the Mask R-CNN framework, and to detect fracture location indog and cat tibia fractures faster and with higher performance. With the hybrid study, it will be ensured that veterinarians help diagnosefractures on the tibia with higher accuracy by using a computerized system. In this study, a total of 518 dog and cat fracture tibia images thatobtained from universities and institutions were used. F1 score value of this study on total dataset was found to be 85.8%. F1 score valueof this study on dog dataset was found to be 87.8%. F1 score value of this study on cat dataset was found to be 77.7%. With the developedhybrid system, it was determined that the localization of the fracture in an average tibia image took 2.88 seconds. The results of the studyshowed that the hybrid system developed would be beneficial in terms of protecting animal health by making more successful and fasterdetections than the original Mask R-CNN architecture
AU  - BARIŞÇI, Necaattin
AU  - Unver, Halil Murat
AU  - Baydan, Berker
DO  - 10.9775/kvfd.2021.25486
PY  - 2021
JO  - Kafkas Üniversitesi Veteriner Fakültesi Dergisi
VL  - 27
IS  - 3
SN  - 1300-6045
SP  - 347
EP  - 353
DB  - TRDizin
UR  - http://search/yayin/detay/447873
ER  -