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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  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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 online resource (174 p.)
Soggetto topico History of engineering and technology
Soggetto non controllato adaptive threshold
aluminum alloy wheel
basalt fibers
chaotic behavior
composite damage
composite laminate
composites
cross-ply fiber reinforced composite
damage assessment
Damage Index
debonding
defect
defect detection
defect localization
delamination
diffuse ultrasonic waves
discrete defects
electromagnetic detection
electromechanical impedance
FEM simulation
Finite Element Method
frescoed surfaces
historical masonry building
image enhancement
impact damage
impact hammer test
infrared thermography testing
Lamb wave
laser ultrasonic imaging
lock-in thermography
magnetic flux density
morphological reconstruction
n/a
non-destructive damage detection
non-destructive inspection
non-destructive test
non-destructive testing evaluation
non-destructive tests
nondestructive testing
nondestructive testing (NDT)
optical detection
Passive Magnetic Inspection (PMI)
phased array ultrasonic
piezoelectric
plaster detachment
polyamide
polypropylene
probability paper method
rebar
recurrence plot (RP)
recurrence quantification analysis (RQA)
reinforce concrete
residual properties
review
self-magnetic behavior
signal sensitivity
statistical results
steel wire ropes
thick multilayer composites
ultrasonic guided wave
ultrasonic pulse echo
ultrasonic testing
X-ray
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557301203321
Meola Carosena  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui