Separable Confident Transductive Learning for Dairy Cows Teat-End Condition Classification
Teat-end health assessments are crucial to maintain milk quality and dairy cow health. One approach to automate teat-end health assessments is by using a convolutional neural network to classify the magnitude of teat-end alterations based on digital images. This approach has been demonstrated as fea...
Main Authors: | Youshan Zhang, Ian R. Porter, Matthias Wieland, Parminder S. Basran |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-03-01
|
Series: | Animals |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-2615/12/7/886 |
Similar Items
-
Sensor-Based Detection of the Severity of Hyperkeratosis in the Teats of Dairy Cows
by: Susanne Demba, et al.
Published: (2018-11-01) -
Differences between Jersey and Holstein cows in milking-induced teat prolongation during lactation
by: Matúš Gašparík, et al.
Published: (2019-10-01) -
Complex Relationships between Milking-Induced Changes in Teat Structures and Their Pre-Milking Dimensions in Holstein Cows
by: Matúš Gašparík, et al.
Published: (2023-03-01) -
Unsupervised Few Shot Key Frame Extraction for Cow Teat Videos
by: Youshan Zhang, et al.
Published: (2022-05-01) -
Prevalence and risk factors of teat end hyperkeratosis in cows from the Urals region of Russia
by: A.S. Barkova, et al.
Published: (2022-01-01)