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Biometric Systems
Biometric Systems
Autore Nanni Loris
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (352 p.)
Soggetto topico Technology: general issues
Soggetto non controllato online signature verification
shape contexts
function features
SC-DTW
symbolic representation
two-stage method
finger features
multimodal recognition
local coding
Gabor filter
LGS
human identification
biomarker
ECG
machine learning
Physionet
Lviv Biometric Dataset
biometry
identification
bloodstream
image recognition
multi-biometrics
bit planes
block
mutual information
cross-device
dorsal hand vein recognition
person re-identification
superpixel
temporally aligned pooling
walking cycle
automatic recognition
face
voice
body motion
autism spectrum disorder (ASD)
assessment
intervention
curve similarity
curve similarity model
curve similarity transformation
similarity distance
segmentation matching
evolutionary computation
finger vein recognition
hand vein recognition
contactless acquisition device
public vascular pattern dataset
biometric recognition performance evaluation
face verification
optical correlation
Hausdorff distance
image classification
face detection
depth map ensemble
filtering
geometric deep learning
ear detection
structured prediction
semantic segmentation
rotation equivariance
Gaussian mixture model
superpixels
face recognition systems
person identification
biometric systems
survey
automatic signature verification
touch-screen sensor
data quality
enrollment phase
performance assessment
augmented signature
security enhancement
mobile conditions
biometric recognition
visible light iris images
image quality assessment
image covariates
quality filtering
vascular biometric recognition
wrist vein recognition
contactless dataset
pattern recognition
infrared camera
non-contact devices
Scale-Invariant Feature Transform (SIFT®)
Speeded Up Robust Features (SURF®)
Oriented FAST and Rotated BRIEF (ORB)
fingerprint
presentation attack detection
deep learning
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557789403321
Nanni Loris  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Statistical Machine Learning for Human Behaviour Analysis
Statistical Machine Learning for Human Behaviour Analysis
Autore Moeslund Thomas
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (300 p.)
Soggetto topico History of engineering & technology
Soggetto non controllato multi-objective evolutionary algorithms
rule-based classifiers
interpretable machine learning
categorical data
hand sign language
deep learning
restricted Boltzmann machine (RBM)
multi-modal
profoundly deaf
noisy image
ensemble methods
adaptive classifiers
recurrent concepts
concept drift
stock price direction prediction
toe-off detection
gait event
silhouettes difference
convolutional neural network
saliency detection
foggy image
spatial domain
frequency domain
object contour detection
discrete stationary wavelet transform
attention allocation
attention behavior
hybrid entropy
information entropy
single pixel single photon image acquisition
time-of-flight
action recognition
fibromyalgia
Learning Using Concave and Convex Kernels
Empatica E4
self-reported survey
speech emotion recognition
3D convolutional neural networks
k-means clustering
spectrograms
context-aware framework
accuracy
false negative rate
individual behavior estimation
statistical-based time-frequency domain and crowd condition
emotion recognition
gestures
body movements
Kinect sensor
neural networks
face analysis
face segmentation
head pose estimation
age classification
gender classification
singular point detection
boundary segmentation
blurring detection
fingerprint image enhancement
fingerprint quality
speech
committee of classifiers
biometric recognition
multimodal-based human identification
privacy
privacy-aware
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557288403321
Moeslund Thomas  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui