top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Data Science and Knowledge Discovery
Data Science and Knowledge Discovery
Autore Portela Filipe
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (254 p.)
Soggetto topico Information technology industries
Computer science
Soggetto non controllato crisis reporting
chatbots
journalists
news media
COVID-19
textbook research
digital humanities
digital infrastructures
data analysis
content base image retrieval
semantic information retrieval
deep features
multimedia document retrieval
data science
open government data
governance and social institutions
economic determinants of open data
geoinformation technology
fractal dimension
territorial road network
box-counting framework
script Python
ArcGIS
internet of things
LoRaWAN
ICT
The Things Network
ESP32 microcontroller
decision systems
rule based systems
databases
rough sets
prediction by partial matching
spatio-temporal
activity recognition
smart homes
artificial intelligence
automation
e-commerce
machine learning
big data
customer relationship management (CRM)
distracted driving
driving behavior
driving operation area
data augmentation
feature extraction
authorship
text mining
attribution
neural networks
deep learning
forensic intelligence
dashboard
WebGIS
data analytics
SARS-CoV-2
Big Data
Web Intelligence
media analytics
social sciences
humanities
linked open data
adaptation process
interdisciplinary research
media criticism
classification
information systems
public health
data mining
ioCOVID19
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910576878103321
Portela Filipe  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Sensing and Signal Processing in Smart Healthcare
Sensing and Signal Processing in Smart Healthcare
Autore Zhao Wenbing
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (198 p.)
Soggetto topico Language
English language teaching (ELT)
Soggetto non controllato smart homes
Internet of Things (IoT)
Wi-Fi
human monitoring
behavioral analysis
ambient assisted living
intelligent luminaires
wireless sensor network
indoor localisation
indoor monitoring
Graphics Processing Units (GPUs)
CUDA
OpenMP
OpenCL
K-means
brain cancer detection
hyperspectral imaging
unsupervised clustering
impaired sensor
Structural Health Monitoring
Time of Flight
subharmonics
Cascaded-Integrator-Comb (CIC) filter
FPGA
fixed point math
data adaptive demodulator
motion estimation
inertial sensors
simulation
spline function
Kalman filter
eHealth
software engineering
gesture recognition
Dynamic Time Warping
Hidden Markov Model
usability
Cramér-Rao lower bound (CRLB)
human motion
Inertial Measurement Unit (IMU)
Time of Arrival (TOA)
wearable sensors
endothelial dysfunction
photoplethysmography
machine learning
computer-assisted screening
sleep pose recognition
keypoints feature matching
Bayesian inference
near-infrared images
scale invariant feature transform
heartbeat classification
arrhythmia
denoising autoencoder
autoencoder
deep learning
auditory perception
biometrics
computer vision
web control access
web security
human-computer interaction
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557483503321
Zhao Wenbing  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui