首页|Research from Massey University Yields New Study Findings on Machine Learning [The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behaviour al Identification in Domestic Dogs (* * Canis familiaris* * ): A Validation Stud y]
Research from Massey University Yields New Study Findings on Machine Learning [The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behaviour al Identification in Domestic Dogs (* * Canis familiaris* * ): A Validation Stud y]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting out of Palmerston, New Zealand, by New sRx editors, research stated, “Assessing the behaviour and physical attributes o f domesticated dogs is critical for predicting the suitability of animals for co mpanionship or specific roles such as hunting, military or service.” Funders for this research include Healthy Pets New Zealand; Centre For Canine Nu trition, Massey University. The news correspondents obtained a quote from the research from Massey Universit y: “Common methods of behavioural assessment can be time consuming, labour-inten sive, and subject to bias, making large-scale and rapid implementation challengi ng. Objective, practical and time effective behaviour measures may be facilitate d by remote and automated devices such as accelerometers. This study, therefore, aimed to validate the ActiGraph® accelerometer as a tool for behavioural classification. This study used a machi ne learning method that identified nine dog behaviours with an overall accuracy of 74% (range for each behaviour was 54 to 93%). In a ddition, overall body dynamic acceleration was found to be correlated with the a mount of time spent exhibiting active behaviours (barking, locomotion, scratchin g, sniffing, and standing; R2 = 0.91, * * p* * <0.001).”
Massey UniversityPalmerstonNew Zeala ndAustralia and New ZealandAlgorithmsCyborgsEmerging TechnologiesMachi ne Learning
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