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Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland –

Information technology industries --- Traffic sign detection and tracking (TSDR) --- advanced driver assistance system (ADAS) --- computer vision --- 3D convolutional neural networks --- machine learning --- CT brain --- brain hemorrhage --- visual inspection --- one-class classifier --- grow-when-required neural network --- evolving connectionist systems --- automatic design --- bio-inspired techniques --- artificial bee colony --- image analysis --- feature extraction --- ship classification --- marine systems --- citrus --- pests and diseases identification --- convolutional neural network --- parameter efficiency --- vehicle detection --- YOLOv2 --- focal loss --- anchor box --- multi-scale --- deep learning --- neural network --- generative adversarial network --- synthetic images --- tool wear monitoring --- superalloy tool --- image recognition --- object detection --- UAV imagery --- vehicular traffic flow detection --- vehicular traffic flow classification --- vehicular traffic congestion --- video classification --- benchmark --- semantic segmentation --- atrous convolution --- spatial pooling --- ship radiated noise --- underwater acoustics --- surface electromyography (sEMG) --- convolution neural networks (CNNs) --- hand gesture recognition --- fabric defect --- mixed kernels --- cross-scale --- cascaded center-ness --- deformable localization --- continuous casting --- surface defects --- 3D imaging --- defect detection --- object detector --- object tracking --- activity measure --- Yolo --- deep sort --- Hungarian algorithm --- optical flows --- spatiotemporal interest points --- sports scene --- CT images --- convolutional neural networks --- hepatic cancer --- visual question answering --- three-dimensional (3D) vision --- reinforcement learning --- human–robot interaction --- few shot learning --- SVM --- CNN --- cascade classifier --- video surveillance --- RFI --- artefacts --- InSAR --- image processing --- pixel convolution --- thresholding --- nearest neighbor filtering --- data acquisition --- augmented reality --- pose estimation --- industrial environments --- information retriever sensor --- multi-hop reasoning --- evidence chains --- complex search request --- high-speed trains --- hunting --- non-stationary --- feature fusion --- multi-sensor fusion --- unmanned aerial vehicles --- drone detection --- UAV detection --- visual detection --- n/a --- human-robot interaction

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Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland –

Information technology industries --- Traffic sign detection and tracking (TSDR) --- advanced driver assistance system (ADAS) --- computer vision --- 3D convolutional neural networks --- machine learning --- CT brain --- brain hemorrhage --- visual inspection --- one-class classifier --- grow-when-required neural network --- evolving connectionist systems --- automatic design --- bio-inspired techniques --- artificial bee colony --- image analysis --- feature extraction --- ship classification --- marine systems --- citrus --- pests and diseases identification --- convolutional neural network --- parameter efficiency --- vehicle detection --- YOLOv2 --- focal loss --- anchor box --- multi-scale --- deep learning --- neural network --- generative adversarial network --- synthetic images --- tool wear monitoring --- superalloy tool --- image recognition --- object detection --- UAV imagery --- vehicular traffic flow detection --- vehicular traffic flow classification --- vehicular traffic congestion --- video classification --- benchmark --- semantic segmentation --- atrous convolution --- spatial pooling --- ship radiated noise --- underwater acoustics --- surface electromyography (sEMG) --- convolution neural networks (CNNs) --- hand gesture recognition --- fabric defect --- mixed kernels --- cross-scale --- cascaded center-ness --- deformable localization --- continuous casting --- surface defects --- 3D imaging --- defect detection --- object detector --- object tracking --- activity measure --- Yolo --- deep sort --- Hungarian algorithm --- optical flows --- spatiotemporal interest points --- sports scene --- CT images --- convolutional neural networks --- hepatic cancer --- visual question answering --- three-dimensional (3D) vision --- reinforcement learning --- human–robot interaction --- few shot learning --- SVM --- CNN --- cascade classifier --- video surveillance --- RFI --- artefacts --- InSAR --- image processing --- pixel convolution --- thresholding --- nearest neighbor filtering --- data acquisition --- augmented reality --- pose estimation --- industrial environments --- information retriever sensor --- multi-hop reasoning --- evidence chains --- complex search request --- high-speed trains --- hunting --- non-stationary --- feature fusion --- multi-sensor fusion --- unmanned aerial vehicles --- drone detection --- UAV detection --- visual detection --- n/a --- human-robot interaction

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Advanced intelligent (ADI) control through Versatile Intelligent Portable (VIP) Platforms is a rapidly developing, complex, challenging field with great practical importance and potential. ADI control is an interdisciplinary field which combines and extends theories and methods from control theory, computer science, and operations research areas with the aim of developing controllers that are highly adaptable to significant unanticipated changes. Deep research and communicating new trends in the design, control, and applications of the real time control of intelligent sensors systems using advanced intelligent control methods and techniques is the main purpose of this book. Innovative multi-sensor fusion techniques, integrated through VIP platforms, are developed and combined with computer vision, virtual and augmented reality (VR&AR), and intelligent communication, including remote control, adaptive sensor networks, human–robot (H2R) interaction systems, and machine-to-machine (M2M) interfaces. Intelligent decision support systems (IDSS), including remote sensing, and their integration with DSS, GA-based DSS, fuzzy sets DSS, rough set-based DSS, intelligent agent-assisted DSS, process mining integration into decision support, adaptive DSS, computer vision-based DSS, and sensory and robotic DSS are highlighted in the field of advanced intelligent control. Approaching new technologies using advanced intelligent control through versatile intelligent portable platforms involves complex multidisciplinary research covering enhanced IoT technologies and applications in the 5G densification era, bio-inspired techniques in future manufacturing enterprise control, cyberphysical systems approach to cognitive enterprise, developing the IT Industry 4.0 concept, industrial systems in the digital age, cloud computing, robotics, and automation with applications such as human aid mechatronics moving in unstructured and uneven environments, rescue robots, firefighting robots, rehabilitation robots, robot-assisted surgery, and domestic robots.

Passive Brain Signals --- adaptive automation and controller --- EOG artifact --- independent component analysis --- engagement index --- lower limb --- rehabilitation robot --- motion intention acquisition --- static torque sensor --- quadcopter --- drone --- pollutant --- carbon --- air monitoring --- kernel --- cyber-physical systems --- intelligent cyber enterprise --- systems interface --- user experience --- accessibility --- autism spectrum disorder --- game-based learning --- systematic literature review --- exoskeleton hand --- fractional order model --- control --- human–robot interaction --- training task --- multi-sensor system --- quantum particle swarm optimization --- support vector machines --- microinjection sensor --- PDMS capillary --- micro-wire --- picolitre volume measurement --- MPWM microfluidic transport --- β-Ga2O3 --- nanowires --- oxidation --- silver catalyst --- electrical conductivity --- photodetector --- automatic distortion rectification --- wide-angle lens --- fish-eye lens --- advanced driver-assistance system (ADAS) --- video-surveillance --- vision tasks --- connected bike --- smart technologies --- IoT --- personalized training --- embedded --- back-end --- front-end --- Android --- modules --- MQTT --- monitoring --- 3D scanning --- 3D shape reconstruction --- RGB-D sensors --- imperfect data --- hybrid neural networks --- computer vision --- deep learning --- convolutional neural networks --- advanced intelligent control --- facial emotion recognition --- face recognition --- NAO robot --- critical infrastructures --- positioning system --- optical measurements --- fiducial markers --- adaptive kalman --- measurement fusion --- software sensor data --- machine-learning classifier --- smartphone security --- intelligent control --- robot control intelligent sensor systems --- intelligent decision support systems --- versatile intelligent portable platforms --- new technologies --- adaptive sensor networks --- virtual and augmented reality --- intelligent remote control and communication