CCTV footage of beef cattle segmented into individual instances.
problem Early detection of animal welfare issues in beef cattle.
method Transformed a fully convolutional network into an instance segmentation network.
result Network outputs a single prediction for every animal in CCTV footage.
Deep learning classifies animal behavior from wearable accelerometers.
problem Classifying animal behavior from accelerometer data.
method End-to-end deep neural network with IIR and FIR filters.
result Outperforms state-of-the-art algorithms in real-time classification.
Study models live cattle futures prices in Brazil.
problem Estimate futures prices for better risk management.
method Holt-Winters, ARIMA, GARMA models.
result GARMA(2,1) model best predicts BGI prices.
AI helps assess nature-related financial risks for financial institutions.
problem Challenges in evaluating nature-related risks due to large data volume and complexity.
method Uses AI to address data gaps, uncertainty, and complex systems.
result Potential AI solutions for two use cases: beef supply and water utility.
We analyze the market efficiency of 25 commodity futures across various groups -- metals, energies, softs, grains and other agricultural commodities. To do so, we utilize recently proposed Efficiency Index to find that the most efficient of all the analyzed commodities is heating oil, closely followed by WTI crude oil,…
Researchers develop a machine learning model to improve smell perception for food quality monitoring.
problem Limited data in target domain makes it hard to accurately classify food quality.
method Weakly supervised domain adaptation framework using multiple models in supervised and unsupervised settings.
result The approach generalizes well from one domain to another, improving food quality classification.
Market trade-routes can support infectious-disease transmission, impacting biological populations and even disrupting causal trade. Epidemiological models increasingly account for reductions in infectious contact, such as risk-aversion behaviour in response to pathogen outbreaks. However, market dynamics clearly differ…
Machine learning improves diagnostic test accuracy for bovine tuberculosis.
problem Improving diagnostic test sensitivity for bovine tuberculosis.
method Machine learning to assess risk landscapes and predict infection.
result Test sensitivity improved, detecting 240 more infected herds per year.
Neural network solves inverse problem in multiscale mechanics.
problem Identifying elastic properties of random materials.
method Artificial neural networks trained on processed databases.
result Robust identification method validated with synthetic and real data.