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Entropy in Image Analysis III



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Autore: Sparavigna Amelia Carolina Visualizza persona
Titolo: Entropy in Image Analysis III Visualizza cluster
Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica: 1 online resource (230 p.)
Soggetto topico: History of engineering and technology
Technology: general issues
Soggetto non controllato: anode heel effect
bat optimization
cellular neural network
chaos
circular-step wedge
color image encryption
computed tomography
computer-assisted diagnosis
continuous-time image reconstruction
contrast-detail
cryptanalysis
diffusion
entropy
fwi
gamma correction
Hilbert curve
HSV color space
human crowd behavior (HCB)
hyper-chaotic
hyperchaotic
image and video compression
image encryption
image encryption/decryption
image enhancement
image segmentation
improved entropy (IE)
inverse problems
iterative reconstruction
Jaccard similarity
low-light image
machine learning
maximum-likelihood expectation-maximization method
multi-person counting
multiple bit operation
mutual information
n/a
Newton-Raphson's method
particles gradient motion (PGM)
permutation
power-divergence measure
prior information
regularization
Retinex
ribonucleic acid
run-length-based entropy coding
scan route
secure communication
security analysis
speeded up robust features (SURF)
spleen injury detection
transformed Zigzag
visible ratio
Persona (resp. second.): SparavignaAmelia Carolina
Sommario/riassunto: Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future.
Titolo autorizzato: Entropy in Image Analysis III  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910566462103321
Lo trovi qui: Univ. Federico II
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