Canine age classification using Deep Learning as a step towards preventive medicine in animals

• Autorzy: Mazurek, Szymon , Wielgosz, Maciej , Caputa, Jakub , Frączek, Rafał , Karwatowski, Michał , Grzeszczyk, Jakub , Łukasik, Daria , Śmiech, Anna , Russek, Paweł , Jamro, Ernest , Dąbrowska-Boruch, Agnieszka , Pietroń, Marcin , Sebastian, Koryciak , Wiatr, Kazimierz
• Języki publikacji: EN

Abstrakty

EN

The main goal of this work was to implement a reliable machine learning algorithm that can classify the age of a dog, given only a photograph of its face. The problem, which seems simple for humans, presents itself as very difficult for the machine learning algorithms due to differences of facial features among the dogs population. As convolutional neural networks (CNNs) performed poorly in this problem, authors took other approach of creating novel architecture consisting of combination of CNN and vision transformer (ViT) and examining the age of the dogs separately for every breed. Authors were able to achieve better results than those in initial works covering the problem.

• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2022
• Tom: Vol. 30
• Strony: 169--172
• Opis fizyczny: Bibliogr. 11 poz.

Twórcy

autor

Mazurek, Szymon

autor

Wielgosz, Maciej

autor

Caputa, Jakub

autor

Frączek, Rafał

autor

Karwatowski, Michał

autor

Grzeszczyk, Jakub

autor

Łukasik, Daria

autor

Śmiech, Anna

autor

Russek, Paweł

autor

Jamro, Ernest

autor

Dąbrowska-Boruch, Agnieszka

autor

Pietroń, Marcin

autor

Sebastian, Koryciak

autor

Wiatr, Kazimierz

Identyfikatory

DOI

10.15439/2022F226