Zobrazeno 1 - 10
of 246
pro vyhledávání: '"DA Henry"'
Publikováno v:
Remote Sensing; Volume 13; Issue 4; Pages: 603
Remote Sensing, Vol 13, Iss 603, p 603 (2021)
Remote Sensing, Vol 13, Iss 603, p 603 (2021)
Effective dairy farm management requires the regular estimation and prediction of pasture biomass. This study explored the suitability of high spatio-temporal resolution Sentinel-2 imagery and the applicability of advanced machine learning techniques
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98c6f8bea18bfc0d501fea0101481e2d
Autor:
Ashfaqur Rahman, DA Henry, Md. Sumon Shahriar, Richard Rawnsley, James Hills, Mark J. Freeman, Greg Bishop-Hurley, Daniel Smith
Publikováno v:
Computers and Electronics in Agriculture. 128:20-26
We developed a heat detection algorithm for pasture-based dairy cows.Our algorithm uses data from accelerometer attached to the cow collars.We present the overall accuracy of 82-100% with 100% sensitivity. This study was conducted to investigate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::619007ed3fcb474b86da4407972f846f
https://doi.org/10.1016/j.compag.2016.08.009
https://doi.org/10.1016/j.compag.2016.08.009
Autor:
DA Henry, James Hills, Richard Rawnsley, Greg Timms, Greg Bishop-Hurley, Ritaban Dutta, Daniel Smith
Publikováno v:
Computers and Electronics in Agriculture. 111:18-28
Cattle behavioural classification using cattle tag and supervised ensemble classifiers.Unsupervised hybrid clustering used to study inherent natural grouping in data set.Best classification accuracy was 96% using the bagging ensemble with Tree learne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b6ac2044123982ca0cca455b335481b
https://doi.org/10.1016/j.compag.2014.12.002
https://doi.org/10.1016/j.compag.2014.12.002
Publikováno v:
IJCNN
A study is presented comparing the effectiveness of unsupervised feature representations with handcrafted features for cattle behaviour classification. Precision management of cattle requires the interaction of individual animals to be continuously m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15f54f8e5ff1d9c72020c436c8c9f06e
https://doi.org/10.1109/ijcnn.2016.7727573
https://doi.org/10.1109/ijcnn.2016.7727573
Autor:
Richard Rawnsley, Mark J. Freeman, Greg Bishop-Hurley, Md. Sumon Shahriar, James Hills, Daniel Smith, Ashfaqur Rahman, DA Henry
Publikováno v:
2015 IEEE SENSORS.
The detection of heat (estrus) events in pasture-based dairy cows fitted with on-animal sensors was investigated using an unsupervised learning. Accelerometer data from the cow collar sensors were used in this approach where the aim was to identify i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18830ad7087d86f71d5ddd4844c3aaa3
https://doi.org/10.1109/icsens.2015.7370528
https://doi.org/10.1109/icsens.2015.7370528
Autor:
Ashfaqur Rahman, Greg Bishop-Hurley, Claire D'Este, DA Henry, James Hills, Greg Timms, Daniel Smith, Ahsan Morshed, Andrew D. Hellicar, Richard Rawnsley, Yanfeng Shu, Ritaban Dutta
Publikováno v:
I2MTC
An experiment to study the impact of supplements upon the feeding behavior of dairy cattle was conducted at the Tasmanian Institute of Agriculture (TIA) Dairy Research Facility. Collar systems with 3-axis accelerometer and magnetometer were fitted to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fad923b49cca6c77330f102437177b7d
https://doi.org/10.1109/i2mtc.2014.6860952
https://doi.org/10.1109/i2mtc.2014.6860952
Publikováno v:
Animal Production Science. 54:1687
Monitoring and management of grazing livestock production systems can be enhanced with remote monitoring technologies collecting information with high temporal and spatial detail. However, the potential benefits of such technologies have yet to be re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86353f44d2f76e5d86b7f22739ac8d58
https://doi.org/10.1071/an14368
https://doi.org/10.1071/an14368