LEADER 04919nam 2201189z- 450 001 9910576879803321 005 20231214133237.0 035 $a(CKB)5720000000008377 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/84508 035 $a(EXLCZ)995720000000008377 100 $a20202206d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 electronic resource (228 p.) 311 $a3-0365-4035-0 311 $a3-0365-4036-9 330 $aAnimal production (e.g., milk, meat, and eggs) provides valuable protein production for human beings and animals. However, animal production is facing several challenges worldwide such as environmental impacts and animal welfare/health concerns. In animal farming operations, accurate and efficient monitoring of animal information and behavior can help analyze the health and welfare status of animals and identify sick or abnormal individuals at an early stage to reduce economic losses and protect animal welfare. In recent years, there has been growing interest in animal welfare. At present, sensors, big data, machine learning, and artificial intelligence are used to improve management efficiency, reduce production costs, and enhance animal welfare. Although these technologies still have challenges and limitations, the application and exploration of these technologies in animal farms will greatly promote the intelligent management of farms. Therefore, this Special Issue will collect original papers with novel contributions based on technologies such as sensors, big data, machine learning, and artificial intelligence to study animal behavior monitoring and recognition, environmental monitoring, health evaluation, etc., to promote intelligent and accurate animal farm management. 606 $aTechnology: general issues$2bicssc 606 $aHistory of engineering & technology$2bicssc 610 $apig weight 610 $abody size 610 $aestimation 610 $adeep learning 610 $aconvolutional neural network 610 $apig identification 610 $amask scoring R-CNN 610 $asoft-NMS 610 $agroup-housed pigs 610 $aaudio 610 $adairy cow 610 $amastication 610 $ajaw movement 610 $aforage management 610 $aprecision livestock management 610 $aequine behavior 610 $awearable sensor 610 $aintermodality interaction 610 $aclass-balanced focal loss 610 $aabsorbing Markov chain 610 $acow behavior analysis 610 $aprediction of calving time 610 $acow identification 610 $aEfficientDet 610 $aYOLACT++ 610 $acascaded model 610 $ainstance segmentation 610 $agenerative adversarial network 610 $amachine learning 610 $aautomated medical image processing 610 $adeep neural network 610 $aanimal science 610 $aCT scans 610 $acomputer vision 610 $acow 610 $aextensive livestock 610 $asensorized wearable device 610 $amonitoring 610 $aparturition prediction 610 $aradar sensors 610 $aradar signal processing 610 $aanimal farming 610 $acomputational ethology 610 $asignal classification 610 $awavelet analysis 610 $adairy welfare 610 $ahierarchical clustering 610 $amutual information 610 $aprecision livestock farming 610 $atime budgets 610 $aunsupervised machine learning 610 $awearables design 610 $aanimal-centered design 610 $aanimal telemetry 610 $amodularity 610 $asmart collar 610 $adesign contributions 610 $aadditive manufacturing 610 $alow-frequency tracking 610 $acommercial aviary 610 $alaying hens 610 $afalse registrations 610 $atree-based classifier 610 $aanimal behaviour 615 7$aTechnology: general issues 615 7$aHistory of engineering & technology 700 $aQiao$b Yongliang$4edt$01324800 702 $aChai$b Lilong$4edt 702 $aHe$b Dongjian$4edt 702 $aSu$b Daobilige$4edt 702 $aQiao$b Yongliang$4oth 702 $aChai$b Lilong$4oth 702 $aHe$b Dongjian$4oth 702 $aSu$b Daobilige$4oth 906 $aBOOK 912 $a9910576879803321 996 $aAdvances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming$93036320 997 $aUNINA