Zobrazeno 1 - 10
of 298
pro vyhledávání: '"Cunningham, Pádraig"'
Autor:
Dissanayake, Oshana, Riaboff, Lucile, McPherson, Sarah E., Kennedy, Emer, Cunningham, Pádraig
In recent years, there has been considerable progress in research on human activity recognition using data from wearable sensors. This technology also has potential in the context of animal welfare in livestock science. In this paper, we report on re
Externí odkaz:
http://arxiv.org/abs/2408.13041
Autor:
Dissanayake, Oshana, McPherson, Sarah E., Allyndree, Joseph, Kennedy, Emer, Cunningham, Padraig, Riaboff, Lucile
Getting new insights on pre-weaned calf behavioral adaptation to routine challenges (transport, group relocation, etc.) and diseases (respiratory diseases, diarrhea, etc.) is a promising way to improve calf welfare in dairy farms. A classic approach
Externí odkaz:
http://arxiv.org/abs/2409.00053
Autor:
Cunningham, Padraig, Smyth, Barry
There has been some concern about the impact of predatory publishers on scientific research for some time. Recently, publishers that might previously have been considered `predatory' have established their bona fides, at least to the extent that they
Externí odkaz:
http://arxiv.org/abs/2408.10262
Autor:
Dissanayake, Oshana, Mcpherson, Sarah E., Allyndrée, Joseph, Kennedy, Emer, Cunningham, Pádraig, Riaboff, Lucile
Publikováno v:
European Conference on Precision Livestock Farming, Sep 2024, Bologne (ITA), Italy
Automatic monitoring of calf behaviour is a promising way of assessing animal welfare from their first week on farms. This study aims to (i) develop machine learning models from accelerometer data to classify the main behaviours of pre-weaned calves
Externí odkaz:
http://arxiv.org/abs/2406.17352
Autor:
Dissanayake, Oshana, McPherson, Sarah E., Allyndree, Joseph, Kennedy, Emer, Cunningham, Padraig, Riaboff, Lucile
Monitoring calf behaviour continuously would be beneficial to identify routine practices (e.g., weaning, dehorning, etc.) that impact calf welfare in dairy farms. In that regard, accelerometer data collected from neck collars can be used along with M
Externí odkaz:
http://arxiv.org/abs/2404.18159
Correlations in streams of multivariate time series data means that typically, only a small subset of the features are required for a given data mining task. In this paper, we propose a technique which we call Merit Score for Time-Series data (MSTS)
Externí odkaz:
http://arxiv.org/abs/2112.03705
A significant impediment to progress in research on bias in machine learning (ML) is the availability of relevant datasets. This situation is unlikely to change much given the sensitivity of such data. For this reason, there is a role for synthetic d
Externí odkaz:
http://arxiv.org/abs/2107.08928
While state-of-the-art NLP models have been achieving the excellent performance of a wide range of tasks in recent years, important questions are being raised about their robustness and their underlying sensitivity to systematic biases that may exist
Externí odkaz:
http://arxiv.org/abs/2106.15231
In Machine Learning, feature selection entails selecting a subset of the available features in a dataset to use for model development. There are many motivations for feature selection, it may result in better models, it may provide insight into the d
Externí odkaz:
http://arxiv.org/abs/2106.06437
Algorithmic Bias can be due to bias in the training data or issues with the algorithm itself. These algorithmic issues typically relate to problems with model capacity and regularisation. This underestimation bias may arise because the model has been
Externí odkaz:
http://arxiv.org/abs/2105.15064