Automated recognition of pain in cats

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversity of Haifa-
Autor(es): dc.contributorThe University of Nottingham-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity of Lincoln-
Autor(es): dc.creatorFeighelstein, Marcelo-
Autor(es): dc.creatorShimshoni, Ilan-
Autor(es): dc.creatorFinka, Lauren R.-
Autor(es): dc.creatorLuna, Stelio P. L.-
Autor(es): dc.creatorMills, Daniel S.-
Autor(es): dc.creatorZamansky, Anna-
Data de aceite: dc.date.accessioned2025-08-21T17:49:51Z-
Data de disponibilização: dc.date.available2025-08-21T17:49:51Z-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2022-11-30-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1038/s41598-022-13348-1-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/241151-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/241151-
Descrição: dc.descriptionFacial expressions in non-human animals are closely linked to their internal affective states, with the majority of empirical work focusing on facial shape changes associated with pain. However, existing tools for facial expression analysis are prone to human subjectivity and bias, and in many cases also require special expertise and training. This paper presents the first comparative study of two different paths towards automatizing pain recognition in facial images of domestic short haired cats (n = 29), captured during ovariohysterectomy at different time points corresponding to varying intensities of pain. One approach is based on convolutional neural networks (ResNet50), while the other—on machine learning models based on geometric landmarks analysis inspired by species specific Facial Action Coding Systems (i.e. catFACS). Both types of approaches reach comparable accuracy of above 72%, indicating their potential usefulness as a basis for automating cat pain detection from images.-
Descrição: dc.descriptionInformation Systems Department University of Haifa-
Descrição: dc.descriptionSchool of Veterinary Medicine and Science The University of Nottingham-
Descrição: dc.descriptionDepartment of Veterinary Surgery and Animal Reproduction School of Veterinary Medicine and Animal Science São Paulo State University (Unesp), São Paulo-
Descrição: dc.descriptionSchool of Life Sciences Joseph Bank Laboratories University of Lincoln-
Descrição: dc.descriptionDepartment of Veterinary Surgery and Animal Reproduction School of Veterinary Medicine and Animal Science São Paulo State University (Unesp), São Paulo-
Idioma: dc.languageen-
Relação: dc.relationScientific Reports-
???dc.source???: dc.sourceScopus-
Título: dc.titleAutomated recognition of pain in cats-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.