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Livestock

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Machine Learning Algorithms to Classify and Quantify Multiple Behaviours in Dairy Calves Using a Sensor: Moving beyond Classification in Precision Livestock.

Sensors (Basel, Switzerland)
Previous research has shown that sensors monitoring lying behaviours and feeding can detect early signs of ill health in calves. There is evidence to suggest that monitoring change in a single behaviour might not be enough for disease prediction. In ...

ASAS-NANP SYMPOSIUM: Applications of machine learning for livestock body weight prediction from digital images.

Journal of animal science
Monitoring, recording, and predicting livestock body weight (BW) allows for timely intervention in diets and health, greater efficiency in genetic selection, and identification of optimal times to market animals because animals that have already reac...

Advancements in sensor technology and decision support intelligent tools to assist smart livestock farming.

Journal of animal science
Remote monitoring, modern data collection through sensors, rapid data transfer, and vast data storage through the Internet of Things (IoT) have advanced precision livestock farming (PLF) in the last 20 yr. PLF is relevant to many fields of livestock ...

Livestock Informatics Toolkit: A Case Study in Visually Characterizing Complex Behavioral Patterns across Multiple Sensor Platforms, Using Novel Unsupervised Machine Learning and Information Theoretic Approaches.

Sensors (Basel, Switzerland)
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 agg...

Object detection and tracking using a high-performance artificial intelligence-based 3D depth camera: towards early detection of African swine fever.

Journal of veterinary science
BACKGROUND: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection a...

The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence.

Animal health research reviews
Livestock welfare assessment helps monitor animal health status to maintain productivity, identify injuries and stress, and avoid deterioration. It has also become an important marketing strategy since it increases consumer pressure for a more humane...

Vision-Based Module for Herding with a Sheepdog Robot.

Sensors (Basel, Switzerland)
Livestock farming is assisted more and more by technological solutions, such as robots. One of the main problems for shepherds is the control and care of livestock in areas difficult to access where grazing animals are attacked by predators such as t...

Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning.

Sensors (Basel, Switzerland)
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 ...

Livestock Identification Using Deep Learning for Traceability.

Sensors (Basel, Switzerland)
Farm livestock identification and welfare assessment using non-invasive digital technology have gained interest in agriculture in the last decade, especially for accurate traceability. This study aimed to develop a face recognition system for dairy f...

Recognizing and monitoring infectious sources of schistosomiasis by developing deep learning models with high-resolution remote sensing images.

Infectious diseases of poverty
BACKGROUND: China is progressing towards the goal of schistosomiasis elimination, but there are still some problems, such as difficult management of infection source and snail control. This study aimed to develop deep learning models with high-resolu...