Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Gabriel Carreira Lencioni"'
Autor:
Gabriel Carreira Lencioni, Rafael Vieira de Sousa, Edson José de Souza Sardinha, Rodrigo Romero Corrêa, Adroaldo José Zanella
Publikováno v:
PLoS ONE, Vol 16, Iss 10, p e0258672 (2021)
The aim of this study was to develop and evaluate a machine vision algorithm to assess the pain level in horses, using an automatic computational classifier based on the Horse Grimace Scale (HGS) and trained by machine learning method. The use of the
Externí odkaz:
https://doaj.org/article/4c07ec742ee14cae9b2ad3a7f908ad23
Autor:
Sofia Broomé, Marcelo Feighelstein, Anna Zamansky, Gabriel Carreira Lencioni, Pia Haubro Andersen, Francisca Pessanha, Marwa Mahmoud, Hedvig Kjellström, Albert Ali Salah
Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go ‘deeper’ than tracking, and address automated recognition of animals’ internal states s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e4dc0396a01324e12f283c53b173a29
https://pub.epsilon.slu.se/30105/
https://pub.epsilon.slu.se/30105/
Autor:
Adroaldo José Zanella, Edson José de Souza Sardinha, Rodrigo Romero Corrêa, Rafael Vieira de Sousa, Gabriel Carreira Lencioni
Publikováno v:
PLoS ONE
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
PLoS ONE, Vol 16, Iss 10, p e0258672 (2021)
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
PLoS ONE, Vol 16, Iss 10, p e0258672 (2021)
The aim of this study was to develop and evaluate a machine vision algorithm to assess the pain level in horses, using an automatic computational classifier based on the Horse Grimace Scale (HGS) and trained by machine learning method. The use of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11bdc4954b69868dea8d6a8ac994e592
https://doi.org/10.1371/journal.pone.0258672
https://doi.org/10.1371/journal.pone.0258672