TY - BOOK ID - 125822604 TI - Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Information technology industries KW - Traffic sign detection and tracking (TSDR) KW - advanced driver assistance system (ADAS) KW - computer vision KW - 3D convolutional neural networks KW - machine learning KW - CT brain KW - brain hemorrhage KW - visual inspection KW - one-class classifier KW - grow-when-required neural network KW - evolving connectionist systems KW - automatic design KW - bio-inspired techniques KW - artificial bee colony KW - image analysis KW - feature extraction KW - ship classification KW - marine systems KW - citrus KW - pests and diseases identification KW - convolutional neural network KW - parameter efficiency KW - vehicle detection KW - YOLOv2 KW - focal loss KW - anchor box KW - multi-scale KW - deep learning KW - neural network KW - generative adversarial network KW - synthetic images KW - tool wear monitoring KW - superalloy tool KW - image recognition KW - object detection KW - UAV imagery KW - vehicular traffic flow detection KW - vehicular traffic flow classification KW - vehicular traffic congestion KW - video classification KW - benchmark KW - semantic segmentation KW - atrous convolution KW - spatial pooling KW - ship radiated noise KW - underwater acoustics KW - surface electromyography (sEMG) KW - convolution neural networks (CNNs) KW - hand gesture recognition KW - fabric defect KW - mixed kernels KW - cross-scale KW - cascaded center-ness KW - deformable localization KW - continuous casting KW - surface defects KW - 3D imaging KW - defect detection KW - object detector KW - object tracking KW - activity measure KW - Yolo KW - deep sort KW - Hungarian algorithm KW - optical flows KW - spatiotemporal interest points KW - sports scene KW - CT images KW - convolutional neural networks KW - hepatic cancer KW - visual question answering KW - three-dimensional (3D) vision KW - reinforcement learning KW - human–robot interaction KW - few shot learning KW - SVM KW - CNN KW - cascade classifier KW - video surveillance KW - RFI KW - artefacts KW - InSAR KW - image processing KW - pixel convolution KW - thresholding KW - nearest neighbor filtering KW - data acquisition KW - augmented reality KW - pose estimation KW - industrial environments KW - information retriever sensor KW - multi-hop reasoning KW - evidence chains KW - complex search request KW - high-speed trains KW - hunting KW - non-stationary KW - feature fusion KW - multi-sensor fusion KW - unmanned aerial vehicles KW - drone detection KW - UAV detection KW - visual detection KW - n/a KW - human-robot interaction UR - https://www.unicat.be/uniCat?func=search&query=sysid:125822604 AB - 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 – ER -