LEADER 04524nam 2201213z- 450 001 9910566484703321 005 20231214132933.0 035 $a(CKB)5680000000037532 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/80994 035 $a(EXLCZ)995680000000037532 100 $a20202205d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning in Sensors and Imaging 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 electronic resource (302 p.) 311 $a3-0365-3753-8 311 $a3-0365-3754-6 330 $aMachine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens. 606 $aTechnology: general issues$2bicssc 606 $aHistory of engineering & technology$2bicssc 610 $astar image 610 $aimage denoising 610 $areinforcement learning 610 $amaximum likelihood estimation 610 $amixed Poisson?Gaussian likelihood 610 $amachine learning-based classification 610 $anon-uniform foundation 610 $astochastic analysis 610 $avehicle?pavement?foundation interaction 610 $aforest growing stem volume 610 $aconiferous plantations 610 $avariable selection 610 $atexture feature 610 $arandom forest 610 $ared-edge band 610 $aon-shelf availability 610 $asemi-supervised learning 610 $adeep learning 610 $aimage classification 610 $amachine learning 610 $aexplainable artificial intelligence 610 $awildfire 610 $arisk assessment 610 $aNaïve bayes 610 $atransmission-line corridors 610 $aimage encryption 610 $acompressive sensing 610 $aplaintext related 610 $achaotic system 610 $aconvolutional neural network 610 $acolor prior model 610 $aobject detection 610 $apiston error detection 610 $asegmented telescope 610 $aBP artificial neural network 610 $amodulation transfer function 610 $acomputer vision 610 $aintelligent vehicles 610 $aextrinsic camera calibration 610 $astructure from motion 610 $aconvex optimization 610 $atemperature estimation 610 $aBLDC 610 $aelectric machine protection 610 $atouchscreen 610 $acapacitive 610 $adisplay 610 $aSNR 610 $astylus 610 $alaser cutting 610 $aquality monitoring 610 $aartificial neural network 610 $aburr formation 610 $acut interruption 610 $afiber laser 610 $asemi-supervised 610 $afuzzy 610 $anoisy 610 $areal-world 610 $aplankton 610 $amarine 610 $aactivity recognition 610 $awearable sensors 610 $aimbalanced activities 610 $asampling methods 610 $apath planning 610 $aQ-learning 610 $aneural network 610 $aYOLO algorithm 610 $arobot arm 610 $atarget reaching 610 $aobstacle avoidance 615 7$aTechnology: general issues 615 7$aHistory of engineering & technology 700 $aNam$b Hyoungsik$4edt$01322435 702 $aNam$b Hyoungsik$4oth 906 $aBOOK 912 $a9910566484703321 996 $aMachine Learning in Sensors and Imaging$93034999 997 $aUNINA