Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Catherine McVey"'
Publikováno v:
Sensors, Vol 22, Iss 21, p 8347 (2022)
Advances in neural networks have garnered growing interest in applications of machine vision in livestock management, but simpler landmark-based approaches suitable for small, early stage exploratory studies still represent a critical stepping stone
Externí odkaz:
https://doaj.org/article/f522e4c5fb5a4d90a8036a6c2fd22226
Publikováno v:
Frontiers in Veterinary Science, Vol 7 (2020)
Sensor technologies allow ethologists to continuously monitor the behaviors of large numbers of animals over extended periods of time. This creates new opportunities to study livestock behavior in commercial settings, but also new methodological chal
Externí odkaz:
https://doaj.org/article/e86970b0aec14b6fabc2da11af70d1cb
Publikováno v:
Sensors, Vol 22, Iss 1, p 1 (2021)
Large and densely sampled sensor datasets can contain a range of complex stochastic structures that are difficult to accommodate in conventional linear models. This can confound attempts to build a more complete picture of an animal’s behavior by a
Externí odkaz:
https://doaj.org/article/e2739cc65175400bbc75b1a193bdaee1
Publikováno v:
Applied Animal Science. 39:99-116
Publikováno v:
Applied Animal Behaviour Science. 242:105426
The transition of housing gestating sows from individual stalls to group pens allows for a greater freedom of movement and social interactions, but it comes with many challenges to ensure group cohesion and safety of all animals. Previous research on
Publikováno v:
Applied Animal Behaviour Science. 230:105073
Chute scoring has been used among beef and dairy operations as a method to gauge the relative phenotypic characteristics of animals based on response to physical restraint. While elements of the cattle chute score, such as tail flicking, exit speed,