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Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) / John Ball, Bo Tang
| Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS) / John Ball, Bo Tang |
| Autore | Ball John |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (344 p.) |
| Soggetto topico | History of engineering and technology |
| 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 |
9783039213764
3039213768 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367757403321 |
Ball John
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Smart Wireless Acoustic Sensor Network Design for Noise Monitoring in Smart Cities
| Smart Wireless Acoustic Sensor Network Design for Noise Monitoring in Smart Cities |
| Autore | Alsina-Pagès Rosa Ma |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (240 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
acoustic event detection
acoustic impedance acoustic sensor design acoustics Adrienne aggregate impact anomalous noise events bearing CNOSSOS-EU contribution analysis damping deep learning detection digital signal processing drill DYNAMAP project dynamic model dynamic noise maps END fan individual impact intermittency ratio long short-term memory low-cost sensors map generation mechanical fault motor multirate filters networks noise noise control noise events noise mapping noise mitigation noise monitoring noise sources outdoors noise p-p sensor p-u sensor pattern public information real-time noise mapping regression analysis RMS road surfaces road traffic noise road traffic noise model safety sensor concept sensor nodes shaft smart cities sound sound level meter stabilization temporal forecast urban and suburban environments urban sites classification vehicle interior noise WASN wireless sensor networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557779403321 |
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Alsina-Pagès Rosa Ma
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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