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Machine Learning in Sensors and Imaging
| Machine Learning in Sensors and Imaging |
| Autore | Nam Hyoungsik |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (302 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
activity recognition
artificial neural network BLDC BP artificial neural network burr formation capacitive chaotic system color prior model compressive sensing computer vision coniferous plantations convex optimization convolutional neural network cut interruption deep learning display electric machine protection explainable artificial intelligence extrinsic camera calibration fiber laser forest growing stem volume fuzzy image classification image denoising image encryption imbalanced activities intelligent vehicles laser cutting machine learning machine learning-based classification marine maximum likelihood estimation mixed Poisson-Gaussian likelihood modulation transfer function Naïve bayes neural network noisy non-uniform foundation object detection obstacle avoidance on-shelf availability path planning piston error detection plaintext related plankton Q-learning quality monitoring random forest real-world red-edge band reinforcement learning risk assessment robot arm sampling methods segmented telescope semi-supervised semi-supervised learning SNR star image stochastic analysis structure from motion stylus target reaching temperature estimation texture feature touchscreen transmission-line corridors variable selection vehicle-pavement-foundation interaction wearable sensors wildfire YOLO algorithm |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566484703321 |
Nam Hyoungsik
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Plug-in Hybrid Electric Vehicle (PHEV) / Joeri VAN Mierlo
| Plug-in Hybrid Electric Vehicle (PHEV) / Joeri VAN Mierlo |
| Autore | VAN Mierlo Joeri |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (230 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
hybrid energy storage system
plug-in hybrid electric vehicle Li-ion battery emerging electric machines lithium-ion capacitor electric vehicles (EVs) efficient energy management strategies for hybrid propulsion systems plug-in hybrid attributional electric vehicle energy system energy efficiency modified one-state hysteresis model air quality adaptive neuron-fuzzy inference system (ANFIS) Markov decision process (MDP) simulated annealing Paris Agreement mobility needs interleaved multiport converte dynamic programming state of health estimation strong track filter LCA modelling consequential losses model voltage vector distribution parallel hybrid electric vehicle electricity mix time-delay input convex optimization lifetime model artificial neural network (ANN) Li(Ni1/3Co1/3Mn1/3)O2 battery battery power CO2 capacity degradation regenerative braking open-end winding novel propulsion systems group method of data handling (GMDH) state of charge Well-to-Wheel energy storage systems including wide bandgap (WBG) technology wide bandgap (WBG) technologies marginal lithium polymer battery life-cycle assessment (LCA) energy management dual inverter lithium-ion battery measurements plug-in hybrid electric vehicles (PHEVs) emerging power electronics Q-learning (QL) fuel consumption characteristics Plugin Hybrid electric vehicle Energy Storage systems meta-analysis range-extender engine-on power reinforcement learning (RL) multi-objective genetic algorithm power sharing energy management strategy power distribution hybrid electric vehicles system modelling |
| ISBN |
9783039214549
3039214543 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367565103321 |
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VAN Mierlo Joeri
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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