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Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)
| Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) |
| Autore | Tang Bo |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (344 p.) |
| Soggetto non controllato |
FPGA
recurrence plot (RP) residual learning neural networks driver monitoring navigation depthwise separable convolution optimization dynamic path-planning algorithms object tracking sub-region cooperative systems convolutional neural networks DSRC VANET joystick road scene convolutional neural network (CNN) multi-sensor p-norm occlusion crash injury severity prediction deep leaning squeeze-and-excitation electric vehicles perception in challenging conditions T-S fuzzy neural network total vehicle mass of the front vehicle electrocardiogram (ECG) communications generative adversarial nets camera adaptive classifier updating Vehicle-to-X communications convolutional neural network predictive Geobroadcast infinity norm urban object detector machine learning automated-manual transition red light-running behaviors photoplethysmogram (PPG) panoramic image dataset parallel architectures visual tracking autopilot ADAS kinematic control GPU road lane detection obstacle detection and classification Gabor convolution kernel autonomous vehicle Intelligent Transport Systems driving decision-making model Gaussian kernel autonomous vehicles enhanced learning ethical and legal factors kernel based MIL algorithm image inpainting fusion terrestrial vehicle driverless drowsiness detection map generation object detection interface machine vision driving assistance blind spot detection deep learning relative speed autonomous driving assistance system discriminative correlation filter bank recurrent neural network emergency decisions LiDAR real-time object detection vehicle dynamics path planning actuation systems maneuver algorithm autonomous driving smart band the emergency situations two-wheeled support vector machine model global region biological vision automated driving |
| ISBN | 3-03921-376-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Machine Learning and Embedded Computing in Advanced Driver Assistance Systems |
| Record Nr. | UNINA-9910367757403321 |
Tang Bo
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nondestructive Testing in Composite Materials
| Nondestructive Testing in Composite Materials |
| Autore | Meola Carosena |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (174 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
reinforce concrete
rebar defect self-magnetic behavior magnetic flux density probability paper method Passive Magnetic Inspection (PMI) aluminum alloy wheel X-ray nondestructive testing defect detection adaptive threshold morphological reconstruction non-destructive inspection laser ultrasonic imaging Lamb wave delamination composite laminate frescoed surfaces non-destructive test plaster detachment impact hammer test historical masonry building thick multilayer composites discrete defects ultrasonic pulse echo nondestructive testing (NDT) recurrence plot (RP) recurrence quantification analysis (RQA) statistical results chaotic behavior phased array ultrasonic composites signal sensitivity diffuse ultrasonic waves cross-ply fiber reinforced composite defect localization non-destructive tests damage assessment residual properties Finite Element Method Damage Index non-destructive damage detection steel wire ropes review electromagnetic detection optical detection ultrasonic guided wave basalt fibers polyamide polypropylene impact damage lock-in thermography ultrasonic testing debonding composite damage electromechanical impedance piezoelectric FEM simulation non-destructive testing evaluation infrared thermography testing image enhancement |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557301203321 |
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Meola Carosena
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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