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Smart Sensors and Devices in Artificial Intelligence
Smart Sensors and Devices in Artificial Intelligence
Autore Zhang Dan
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (336 p.)
Soggetto topico History of engineering & technology
Soggetto non controllato microelectromechanical systems
inertial measurement unit
long short term memory recurrent neural networks
artificial intelligence
deep learning
CNN
LSTM
CO2 welding
molten pool
online monitoring
mechanical sensor
self-adaptiveness
ankle-foot exoskeleton
walking assistance
visual tracking
correlation filter
color histogram
adaptive hedge algorithm
scenario generation
autonomous vehicle
smart sensor and device
wireless sensor networks
task assignment
distributed
reliable
energy-efficient
audification
sensor
visualization
speech to text
text to speech
HF-OTH radar
AIS
radar tracking
data fusion
fuzzy functional dependencies
maritime surveillance
surgical robot end-effector
clamping force estimation
joint torque disturbance observer
PSO-BPNN
cable tension measurement
queue length
roadside sensor
vehicle detection
adverse weather
roadside LiDAR
data processing
air pollution
atmospheric data
IoT
machine learning
RNN
Sensors
smart cities
traffic flow
traffic forecasting
wireless sensor network
fruit condition monitoring
artificial neural network
ethylene gas
banana ripening
unidimensional ACGAN
signal recognition
data augmentation
link establishment behaviors
DenseNet
short-wave radio station
landing gear
adaptive landing
vehicle classification
FBG
smart sensors
outlier detection
local outlier factor
data streams
air quality monitoring
evacuation path
multi-story multi-exit building
temperature sensors
multi-time-slots planning
optimization
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557128403321
Zhang Dan  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Symmetry in Engineering Sciences
Symmetry in Engineering Sciences
Autore Montoya Francisco G
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (220 p.)
Soggetto non controllato edge preserving
fault diagnosis
accessibility
urban traffic planning
sensitivity analysis
graphic modelling
Coalbrookdale (Shropshire)
mobile robot
asymmetry
convexity/concavity
flying buttresses
vibration
time-space network
linearization technique
friction damping
adaptive threshold
ring damper
broad learning model
Hilbert transform
express shipment
symmetry
traffic control
railcar flow distribution
optimization
industrial archaeology
high order urban hospitals (HOUHs)
thin-walled gear
rampant arch
traffic congestion
railway transportation
robots
virtual reconstruction
feature selection
geometric modeling
path search
industrial heritage
weighted mean filter
topology
A* algorithm
traffic forecasting
feature interaction
classification
peaks distribution
rolling bearings
noise detector
3D slicer
inclined plane
computing applications
environmental modeling
extension
service network design
evaluation model
anomaly detection
random forest
local preserving projection
complex networks
computer engineering
electronic devices
BP neural network
mechanical structures
segmentation
lifting wavelet
semi-supervised random forest
railway network
cathedral
local monotonicity
aged
optimum
path planning
local data features
local inflection
conditional mutual information
energy dissipation
support vector machine
variational mode decomposition
Agustín de Betancourt
optimization criteria
tumor
trip impedance based on public transportation
Fisher linear discriminant analysis
synchronization
clustering
geometry
electrical circuits
random value impulse noise
ISBN 3-03921-875-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910367742303321
Montoya Francisco G  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui