LEADER 05099nam 22015373a 450 001 9910367757403321 005 20250203235433.0 010 $a9783039213764 010 $a3039213768 024 8 $a10.3390/books978-3-03921-376-4 035 $a(CKB)4100000010106143 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/52517 035 $a(ScCtBLL)5ddaff7b-c58a-4283-a2a5-6041e89b403d 035 $a(OCoLC)1163849944 035 $a(oapen)doab52517 035 $a(EXLCZ)994100000010106143 100 $a20250203i20192019 uu 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMachine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)$fJohn Ball, Bo Tang 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 210 1$aBasel, Switzerland :$cMDPI,$d2019. 215 $a1 electronic resource (344 p.) 311 08$a9783039213757 311 08$a303921375X 330 $aThis book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR and camera processing, ethics, and communications. Several new datasets are also provided for future research work. Researchers and others interested in these topics will find important advances contained in this book. 606 $aHistory of engineering and technology$2bicssc 610 $aFPGA 610 $arecurrence plot (RP) 610 $aresidual learning 610 $aneural networks 610 $adriver monitoring 610 $anavigation 610 $adepthwise separable convolution 610 $aoptimization 610 $adynamic path-planning algorithms 610 $aobject tracking 610 $asub-region 610 $acooperative systems 610 $aconvolutional neural networks 610 $aDSRC 610 $aVANET 610 $ajoystick 610 $aroad scene 610 $aconvolutional neural network (CNN) 610 $amulti-sensor 610 $ap-norm 610 $aocclusion 610 $acrash injury severity prediction 610 $adeep leaning 610 $asqueeze-and-excitation 610 $aelectric vehicles 610 $aperception in challenging conditions 610 $aT-S fuzzy neural network 610 $atotal vehicle mass of the front vehicle 610 $aelectrocardiogram (ECG) 610 $acommunications 610 $agenerative adversarial nets 610 $acamera 610 $aadaptive classifier updating 610 $aVehicle-to-X communications 610 $aconvolutional neural network 610 $apredictive 610 $aGeobroadcast 610 $ainfinity norm 610 $aurban object detector 610 $amachine learning 610 $aautomated-manual transition 610 $ared light-running behaviors 610 $aphotoplethysmogram (PPG) 610 $apanoramic image dataset 610 $aparallel architectures 610 $avisual tracking 610 $aautopilot 610 $aADAS 610 $akinematic control 610 $aGPU 610 $aroad lane detection 610 $aobstacle detection and classification 610 $aGabor convolution kernel 610 $aautonomous vehicle 610 $aIntelligent Transport Systems 610 $adriving decision-making model 610 $aGaussian kernel 610 $aautonomous vehicles 610 $aenhanced learning 610 $aethical and legal factors 610 $akernel based MIL algorithm 610 $aimage inpainting 610 $afusion 610 $aterrestrial vehicle 610 $adriverless 610 $adrowsiness detection 610 $amap generation 610 $aobject detection 610 $ainterface 610 $amachine vision 610 $adriving assistance 610 $ablind spot detection 610 $adeep learning 610 $arelative speed 610 $aautonomous driving assistance system 610 $adiscriminative correlation filter bank 610 $arecurrent neural network 610 $aemergency decisions 610 $aLiDAR 610 $areal-time object detection 610 $avehicle dynamics 610 $apath planning 610 $aactuation systems 610 $amaneuver algorithm 610 $aautonomous driving 610 $asmart band 610 $athe emergency situations 610 $atwo-wheeled 610 $asupport vector machine model 610 $aglobal region 610 $abiological vision 610 $aautomated driving 615 7$aHistory of engineering and technology 700 $aBall$b John$0660667 702 $aTang$b Bo 801 0$bScCtBLL 801 1$bScCtBLL 906 $aBOOK 912 $a9910367757403321 996 $aMachine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)$94323257 997 $aUNINA