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This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

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

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This book compiles a set of original and innovative papers included in the Special Issue on UAVs for vegetation monitoring, which proves the wide scope of UAVs in very diverse vegetation applications, both in agricultural and forestry scenarios, ranging from the characterization of relevant vegetation features to the detection of plant or crop stressors. New methods and techniques are developed and applied to diverse vegetation scenarios to meet the main challenge of sustainability.

Research & information: general --- UAS --- UAV --- vegetation cover --- multispectral --- land cover --- forest --- Acacia --- Indonesia --- tropics --- vegetation ground cover --- vegetation indices --- agro-environmental measures --- olive groves --- southern Spain --- sUAS --- water stress --- ornamental --- container-grown --- artificial intelligence --- machine learning --- deep learning --- neural network --- visual recognition --- precision agriculture --- canopy cover --- image analysis --- crop mapping --- evapotranspiration (ET) --- GRAPEX --- remote sensing --- Two Source Energy Balance model (TSEB) --- contextual spatial domain/resolution --- data aggregation --- eddy covariance (EC) --- Fusarium wilt --- crop disease --- banana --- multispectral remote sensing --- purple rapeseed leaves --- unmanned aerial vehicle --- U-Net --- plant segmentation --- nitrogen stress --- Glycine max --- RGB --- canopy height --- close remote sensing --- growth model --- curve fitting --- NDVI --- solar zenith angle --- flight altitude --- time of day --- operating parameters --- CNN --- Faster RCNN --- SSD --- Inception v2 --- patch-based CNN --- MobileNet v2 --- detection performance --- inference time --- disease detection --- cotton root rot --- plant-level --- single-plant --- plant-by-plant --- classification --- UAV remote sensing --- crop monitoring --- RGB imagery --- multispectral imagery --- century-old biochar --- semantic segmentation --- random forest --- crop canopy --- multispectral image --- chlorophyll content --- remote sensing technique --- individual plant segmentation --- plant detection --- transfer learning --- maize tassel --- tassel branch number --- convolution neural network --- VGG16 --- plant nitrogen estimation --- vegetation index --- image segmentation --- transpiration --- method comparison --- oil palm --- multiple linear regression --- support vector machine --- artificial neural network --- UAV hyperspectral --- wheat yellow rust --- disease monitoring --- texture --- spatial resolution --- RGB camera --- thermal camera --- drought tolerance --- forage grass --- HSV --- CIELab --- broad-sense heritability --- phenotyping gap --- high throughput field phenotyping --- UAV digital images --- winter wheat biomass --- multiscale textures --- red-edge spectra --- least squares support vector machine --- variable importance --- drone --- hyperspectral --- thermal --- nutrient deficiency --- weed detection --- disease diagnosis --- plant trails

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book compiles a set of original and innovative papers included in the Special Issue on UAVs for vegetation monitoring, which proves the wide scope of UAVs in very diverse vegetation applications, both in agricultural and forestry scenarios, ranging from the characterization of relevant vegetation features to the detection of plant or crop stressors. New methods and techniques are developed and applied to diverse vegetation scenarios to meet the main challenge of sustainability.

Research & information: general --- UAS --- UAV --- vegetation cover --- multispectral --- land cover --- forest --- Acacia --- Indonesia --- tropics --- vegetation ground cover --- vegetation indices --- agro-environmental measures --- olive groves --- southern Spain --- sUAS --- water stress --- ornamental --- container-grown --- artificial intelligence --- machine learning --- deep learning --- neural network --- visual recognition --- precision agriculture --- canopy cover --- image analysis --- crop mapping --- evapotranspiration (ET) --- GRAPEX --- remote sensing --- Two Source Energy Balance model (TSEB) --- contextual spatial domain/resolution --- data aggregation --- eddy covariance (EC) --- Fusarium wilt --- crop disease --- banana --- multispectral remote sensing --- purple rapeseed leaves --- unmanned aerial vehicle --- U-Net --- plant segmentation --- nitrogen stress --- Glycine max --- RGB --- canopy height --- close remote sensing --- growth model --- curve fitting --- NDVI --- solar zenith angle --- flight altitude --- time of day --- operating parameters --- CNN --- Faster RCNN --- SSD --- Inception v2 --- patch-based CNN --- MobileNet v2 --- detection performance --- inference time --- disease detection --- cotton root rot --- plant-level --- single-plant --- plant-by-plant --- classification --- UAV remote sensing --- crop monitoring --- RGB imagery --- multispectral imagery --- century-old biochar --- semantic segmentation --- random forest --- crop canopy --- multispectral image --- chlorophyll content --- remote sensing technique --- individual plant segmentation --- plant detection --- transfer learning --- maize tassel --- tassel branch number --- convolution neural network --- VGG16 --- plant nitrogen estimation --- vegetation index --- image segmentation --- transpiration --- method comparison --- oil palm --- multiple linear regression --- support vector machine --- artificial neural network --- UAV hyperspectral --- wheat yellow rust --- disease monitoring --- texture --- spatial resolution --- RGB camera --- thermal camera --- drought tolerance --- forage grass --- HSV --- CIELab --- broad-sense heritability --- phenotyping gap --- high throughput field phenotyping --- UAV digital images --- winter wheat biomass --- multiscale textures --- red-edge spectra --- least squares support vector machine --- variable importance --- drone --- hyperspectral --- thermal --- nutrient deficiency --- weed detection --- disease diagnosis --- plant trails