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Intelligent Sensors for Human Motion Analysis
| Intelligent Sensors for Human Motion Analysis |
| Autore | Krzeszowski Tomasz |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (382 p.) |
| Soggetto topico |
History of engineering and technology
Technology: general issues |
| Soggetto non controllato |
3D human mesh reconstruction
3D human pose estimation 3D multi-person pose estimation absolute poses action units aggregation function anomaly detection artifact classification artifact detection artificial intelligence assessment Azure Kinect balance Berg Balance Scale BILSTM biometrics camera-centric coordinates computer vision convolutional neural networks COVID-19 cyber-physical systems data augmentation deep learning deep neural network deep-learning development diagnosis elderly EMG F-Formation facial expression recognition facial landmarks fall risk detection features fusion features selection FFNN FMCW fuzzy inference gait analysis gait parameters gait recognition gap filling generalization graph convolutional networks grey wolf optimization GRU human action recognition human motion analysis human motion modelling human tracking Kinect v2 kinematics knowledge measure LSTM machine learning markerless markerless motion capture MFCC modular sensing unit motion capture movement tracking n/a neural networks optical sensing principle particle swarm optimization pattern recognition plantar pressure measurement pose estimation posture detection precedence indicator recognition reconstruction regularized discriminant analysis RGB-D sensors robot rule induction skeletal data socially occupied space telemedicine time series classification vital sign whale optimization algorithm XGBoost Zed 2i |
| ISBN | 3-0365-5074-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619469003321 |
Krzeszowski Tomasz
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Unmanned Aerial Vehicles : Platforms, Applications, Security and Services
| Unmanned Aerial Vehicles : Platforms, Applications, Security and Services |
| Autore | Calafate Carlos Tavares |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (174 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
5G
ArduSim ArUco marker autonomous landing BAN logic blind signature computer vision coverage model energy model FANET firefighting communications FPGA horizon human mobility model IoT LoRaWAN MEC Mutual authentication n/a oil well working condition Privacy real-time detection security sense-and-avoid sort topology control Traceable UAS UAV UAVs UAVs/drones positioning undistortion unmanned aerial vehicle (UAV) Unmanned Aerial Vehicles virtual spring forces vision-based YOLOv3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Unmanned Aerial Vehicles |
| Record Nr. | UNINA-9910557698003321 |
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Calafate Carlos Tavares
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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