Smart Sensors and Devices in Artificial Intelligence |
Autore | Zhang Dan |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (336 p.) |
Soggetto topico | History of engineering & technology |
Soggetto non controllato |
microelectromechanical systems
inertial measurement unit long short term memory recurrent neural networks artificial intelligence deep learning CNN LSTM CO2 welding molten pool online monitoring mechanical sensor self-adaptiveness ankle-foot exoskeleton walking assistance visual tracking correlation filter color histogram adaptive hedge algorithm scenario generation autonomous vehicle smart sensor and device wireless sensor networks task assignment distributed reliable energy-efficient audification sensor visualization speech to text text to speech HF-OTH radar AIS radar tracking data fusion fuzzy functional dependencies maritime surveillance surgical robot end-effector clamping force estimation joint torque disturbance observer PSO-BPNN cable tension measurement queue length roadside sensor vehicle detection adverse weather roadside LiDAR data processing air pollution atmospheric data IoT machine learning RNN Sensors smart cities traffic flow traffic forecasting wireless sensor network fruit condition monitoring artificial neural network ethylene gas banana ripening unidimensional ACGAN signal recognition data augmentation link establishment behaviors DenseNet short-wave radio station landing gear adaptive landing vehicle classification FBG smart sensors outlier detection local outlier factor data streams air quality monitoring evacuation path multi-story multi-exit building temperature sensors multi-time-slots planning optimization |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557128403321 |
Zhang Dan | ||
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Symmetry in Engineering Sciences |
Autore | Montoya Francisco G |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (220 p.) |
Soggetto non controllato |
edge preserving
fault diagnosis accessibility urban traffic planning sensitivity analysis graphic modelling Coalbrookdale (Shropshire) mobile robot asymmetry convexity/concavity flying buttresses vibration time-space network linearization technique friction damping adaptive threshold ring damper broad learning model Hilbert transform express shipment symmetry traffic control railcar flow distribution optimization industrial archaeology high order urban hospitals (HOUHs) thin-walled gear rampant arch traffic congestion railway transportation robots virtual reconstruction feature selection geometric modeling path search industrial heritage weighted mean filter topology A* algorithm traffic forecasting feature interaction classification peaks distribution rolling bearings noise detector 3D slicer inclined plane computing applications environmental modeling extension service network design evaluation model anomaly detection random forest local preserving projection complex networks computer engineering electronic devices BP neural network mechanical structures segmentation lifting wavelet semi-supervised random forest railway network cathedral local monotonicity aged optimum path planning local data features local inflection conditional mutual information energy dissipation support vector machine variational mode decomposition Agustín de Betancourt optimization criteria tumor trip impedance based on public transportation Fisher linear discriminant analysis synchronization clustering geometry electrical circuits random value impulse noise |
ISBN | 3-03921-875-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910367742303321 |
Montoya Francisco G | ||
MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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