Computer Vision and Machine Learning for Intelligent Sensing Systems

The reprint offers a selection of high-quality research articles that tackle the major difficulties in computer vision and machine learning for intelligent sensing systems from both theoretical and practical standpoints. This publication includes intelligent sensing techniques, twelve foundational i...

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Bibliografiset tiedot
Aineistotyyppi:	Online
Kieli:	englanti
Julkaistu:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Aiheet:	mobile edge computaing simultaneous wireless information and power transfer energy minimization 5G wireless sensing network IoT fiber bragg grating optical fiber sensor distributed temperature sensor deep learning algorithms fully connected neural network convolutional neural network MADS dataset human segmentation human tracking convolutional neural networks targeted advertising emotion-based recommendation augmented reality computer vision deep learning clustering similarity measure geodesic measure Euclidean measure depth fusion TSDF sensor noises gaze estimation based on feature eye landmark detection self-attention synthetic eye images heuristic attention perceptual grouping self-supervised learning visual representation learning intelligent sensors robotics event-based camera contrast maximization optical flow motion estimation human action recognition graph neural network attention module big five personality traits cultural algorithm hyper-parameter optimization personality perception online self-calibration voxel information n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science
Linkit:	ONIX_20230714_9783036578682_102
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

Kuvaus
Yhteenveto:	The reprint offers a selection of high-quality research articles that tackle the major difficulties in computer vision and machine learning for intelligent sensing systems from both theoretical and practical standpoints. This publication includes intelligent sensing techniques, twelve foundational investigations into sense-making methods, and discusses particular uses of intelligent sensing systems in autonomous driving and virtual reality.

Computer Vision and Machine Learning for Intelligent Sensing Systems

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