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机器学习论文:时间序列分类改善家禽福利(Time Series Classification to Improve Poultry Welfare)

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zycwolf 发表于 5 天前 | 显示全部楼层 |阅读模式
zycwolf 5 天前 129 0 显示全部楼层
机器学习论文:时间序列分类改善家禽福利(Time Series Classification to Improve Poultry Welfare)家禽养殖场是人类食物链的重要贡献者。在全世界范围内,人类为其鸡蛋及其肉类饲养了大量的家禽(例如鸡),提供了丰富的低脂肪蛋白来源。然而,在世界各地,人们越来越关注家禽养殖场的牲畜质量;并且越来越多地要求提高动物福利标准。传感技术和机器学习的最新进展允许自动评估某些鸟类的健康状况,并利用经验教训来改善所有鸟类的福利。鉴于近年来在人类行为分类方面取得了显着进步,并且考虑到人类行为可能更复杂,这项任务表面上看似很容易。然而,正如我们将要证明的那样,对鸡行为进行分类会带来几个独特的挑战,其中主要是从稀疏和嘈杂的数据创建一个可归因的行为词典。在这项工作中,我们引入了一种新颖的时间序列字典学习算法,可以从弱标记的数据源中有力地学习。
Poultry farms are an important contributor to the human food chain.Worldwide, humankind keeps an enormous number of domesticated birds (e.g.chickens) for their eggs and their meat, providing rich sources of low-fatprotein.However, around the world, there have been growing concerns about thequality of life for the livestock in poultry farms;and increasingly vocaldemands for improved standards of animal welfare.Recent advances in sensingtechnologies and machine learning allow the possibility of automaticallyassessing the health of some individual birds, and employing the lessonslearned to improve the welfare for all birds.This task superficially appearsto be easy, given the dramatic progress in recent years in classifying humanbehaviors, and given that human behaviors are presumably more complex.However,as we shall demonstrate, classifying chicken behaviors poses several uniquechallenges, chief among which is creating a generalizable dictionary ofbehaviors from sparse and noisy data.In this work we introduce a novel timeseries dictionary learning algorithm that can robustly learn from weaklylabeled data sources.机器学习论文:时间序列分类改善家禽福利(Time Series Classification to Improve Poultry Welfare) UHt192m0eVR424WW.jpg
URL地址:https://arxiv.org/abs/1811.03149     ----pdf下载地址:https://arxiv.org/pdf/1811.03149    ----机器学习论文:时间序列分类改善家禽福利(Time Series Classification to Improve Poultry Welfare)
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