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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 electronic resource (230 p.)
Soggetto topico: Technology: general issues
History of engineering & technology
Soggetto non controllato: Newton-Raphson's method
chaos
image encryption/decryption
security analysis
image encryption
cryptanalysis
hyper-chaotic
ribonucleic acid
color image encryption
transformed Zigzag
image segmentation
computer-assisted diagnosis
machine learning
spleen injury detection
hyperchaotic
permutation
diffusion
multiple bit operation
circular-step wedge
contrast-detail
mutual information
visible ratio
anode heel effect
prior information
entropy
fwi
regularization
inverse problems
bat optimization
human crowd behavior (HCB)
improved entropy (IE)
Jaccard similarity
multi-person counting
particles gradient motion (PGM)
speeded up robust features (SURF)
Retinex
image enhancement
gamma correction
low-light image
HSV color space
scan route
Hilbert curve
run-length-based entropy coding
image and video compression
secure communication
cellular neural network
power-divergence measure
computed tomography
iterative reconstruction
maximum-likelihood expectation-maximization method
continuous-time image reconstruction
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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