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Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices.

time series analysis --- passive microwave soil moisture --- Sentinel-1 and Sentinel-2 --- Snow Depth and Snow Water Equivalent --- snow cover characteristics --- vegetation biomass --- roughness --- sea ice --- SMOS --- microwave radiometry --- soil moisture downscaling --- Vegetation Biomass --- vegetation index --- Terra MODIS --- Sentinel-1 --- Microwave Indices --- soil moisture content --- dual-frequency ratios --- SMAP --- passive microwave --- water-cloud model --- snow --- Sentinel-1 backscatter --- AMSR2 --- data fusion --- microwaves --- mountain region --- SAR --- start of season --- crops --- NDVI --- scatterometer --- Radarsat-2 --- polarization --- vegetation water content --- co-pol ratio --- active microwaves --- microwave indices --- harvest --- Microwave Radiometry --- soil moisture --- Soil Moisture Content --- snow correlation length --- radiometer --- radar --- soil scattering --- vegetation descriptor --- scale gap --- snow water equivalent

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In order to measure and quantify the complex behavior of real-world systems, either novel mathematical approaches or modifications of classical ones are required to precisely predict, monitor, and control complicated chaotic and stochastic processes. Though the term of entropy comes from Greek and emphasizes its analogy to energy, today, it has wandered to different branches of pure and applied sciences and is understood in a rather rough way, with emphasis placed on the transition from regular to chaotic states, stochastic and deterministic disorder, and uniform and non-uniform distribution or decay of diversity. This collection of papers addresses the notion of entropy in a very broad sense. The presented manuscripts follow from different branches of mathematical/physical sciences, natural/social sciences, and engineering-oriented sciences with emphasis placed on the complexity of dynamical systems. Topics like timing chaos and spatiotemporal chaos, bifurcation, synchronization and anti-synchronization, stability, lumped mass and continuous mechanical systems modeling, novel nonlinear phenomena, and resonances are discussed.

n/a --- nonautonomous (autonomous) dynamical system --- stabilization --- multi-time scale fractional stochastic differential equations --- conditional Tsallis entropy --- wavelet transform --- hyperchaotic system --- Chua’s system --- permutation entropy --- neural network method --- Information transfer --- self-synchronous stream cipher --- colored noise --- Benettin method --- method of synchronization --- topological entropy --- geometric nonlinearity --- Kantz method --- dynamical system --- Gaussian white noise --- phase-locked loop --- wavelets --- Rosenstein method --- m-dimensional manifold --- deterministic chaos --- disturbation --- Mittag–Leffler function --- approximate entropy --- bounded chaos --- Adomian decomposition --- fractional calculus --- product MV-algebra --- Tsallis entropy --- descriptor fractional linear systems --- analytical solution --- fractional Brownian motion --- true chaos --- discrete mapping --- partition --- unbounded chaos --- fractional stochastic partial differential equation --- noise induced transitions --- random number generator --- Fourier spectrum --- hidden attractors --- (asymptotical) focal entropy point --- regular pencils --- continuous flow --- Bernoulli–Euler beam --- image encryption --- Gauss wavelets --- Lyapunov exponents --- discrete fractional calculus --- Lorenz system --- Schur factorization --- discrete chaos --- Wolf method

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This book presents collective works published in the recent Special Issue (SI) entitled " Digital Signal, Image and Video Processing for Emerging Multimedia Technology". These works address the emerging technology in signal processing and its new aspects, as well as the related applications. Recent developments in image/video-based deep learning technology have enabled new services in the field of multimedia and recognition technology. The applications vary and range from digital signal processing to image, video and multimedia signal processing, also including object classification, learning mechanism design and data security. Recent advances in numerical, theoretical and experimental methodologies are presented within the scope of the current book, along with the finding of new learning methods and new methodological developments and their limitations. This book brings together a collection of inter-/multidisciplinary works applied to many classification and data security applications in a coherent manner.

closed circuit television (CCTV) --- character order preserving --- cloud system --- privacy risk --- security --- video surveillance --- 3D --- depth map --- inter-component prediction --- MVD --- reversible data hiding --- texture --- wavelet analysis --- deep learning --- super-resolution --- deep neural architecture --- pattern mining --- multi-scale analysis --- reversible data hiding (RDH) --- image processing --- cloud computing --- public key cryptography (PKC) --- classification --- content–based image retrieval --- genetic algorithms --- image retrieval --- image classification --- Wiener-Granger causality --- block-compressive sensing (BCS) --- saliency --- error analysis --- flexible partitioning --- step-less adaptive sampling --- non-linear filters --- MCV and MLV filters --- de-noising --- noise removal --- edge preserving --- video coding --- motion estimation --- motion compensation --- affine motion model --- perspective motion model --- VVC --- quantization (signal) --- channel allocation --- scalable video coding --- convolution neural network --- scene recognition --- vector of locally aggregated descriptor --- weakly supervised attention map --- fire and smoke detection --- spatial and temporal --- wavelet transform --- coefficient of variation --- image steganalysis --- WOW --- UNIWARD --- ternary classification --- convolutional neural network (CNN) --- bayesian optimization --- gaussian process --- learning rate --- acauisition function --- machine learning --- moving object --- image stabilization --- object detection --- optical flow --- surveillance --- UAVs --- multiview high efficiency video coding --- ρ model --- bit allocation --- rate control --- image similarity --- frame complexity --- image deblurring --- generative adversarial network --- Wasserstein distance --- adversarial loss --- perceptual loss --- sentiment analysis --- social media --- lexicon --- image fusion --- multi-focus --- trimaps --- focus maps --- VisDrone2019 --- aerial imagery --- Faster R-CNN --- SSD --- RFCN --- YOLOv3 --- RetinaNet --- SNIPER --- CenterNet --- wrist-mounted DiverPAD --- electrical insulator --- capacitive touchscreen --- marine leisure activities --- convolutional neural networks --- pattern recognition --- low light --- image restoration --- denoise --- noise reduction --- deep leaning --- multiple feature --- dependency detection --- surveillance system --- n/a --- content-based image retrieval