Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments
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. Computa...
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Woźniak, Marcin edt Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 1 electronic resource (454 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier Open access Unrestricted online access star 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 – English Information technology industries bicssc 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 3-0365-1268-3 3-0365-1269-1 Woźniak, Marcin oth |
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English |
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Woźniak, Marcin |
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Woźniak, Marcin |
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| title |
Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| spellingShingle |
Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| title_full |
Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| title_fullStr |
Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| title_full_unstemmed |
Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| title_auth |
Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| title_new |
Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
| title_sort |
advanced computational intelligence for object detection, feature extraction and recognition in smart sensor environments |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2021 |
| physical |
1 electronic resource (454 p.) |
| isbn |
3-0365-1268-3 3-0365-1269-1 |
| illustrated |
Not Illustrated |
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AT wozniakmarcin advancedcomputationalintelligenceforobjectdetectionfeatureextractionandrecognitioninsmartsensorenvironments |
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Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments |
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