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Artificial Intelligence-Based Learning Approaches for Remote Sensing
| Artificial Intelligence-Based Learning Approaches for Remote Sensing |
| Autore | Jeon Gwanggil |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (382 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Environmental science, engineering & technology |
| Soggetto non controllato |
pine wilt disease dataset
GIS application visualization test-time augmentation object detection hard negative mining video synthetic aperture radar (SAR) moving target shadow detection deep learning false alarms missed detections synthetic aperture radar (SAR) on-board ship detection YOLOv5 lightweight detector remote sensing image spectral domain translation generative adversarial network paired translation synthetic aperture radar ship instance segmentation global context modeling boundary-aware box prediction land-use and land-cover built-up expansion probability modelling landscape fragmentation machine learning support vector machine frequency ratio fuzzy logic artificial intelligence remote sensing interferometric phase filtering sparse regularization (SR) deep learning (DL) neural convolutional network (CNN) semantic segmentation open data building extraction unet deeplab classifying-inversion method AIS atmospheric duct ship detection and classification rotated bounding box attention feature alignment weather nowcasting ResNeXt radar data spectral-spatial interaction network spectral-spatial attention pansharpening UAV visual navigation Siamese network multi-order feature MIoU imbalanced data classification data over-sampling graph convolutional network semi-supervised learning troposcatter tropospheric turbulence intercity co-channel interference concrete bridge visual inspection defect deep convolutional neural network transfer learning interpretation techniques weakly supervised semantic segmentation |
| ISBN | 3-0365-6084-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639984703321 |
Jeon Gwanggil
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Vehicles
| Intelligent Vehicles |
| Autore | Fernández-Llorca David |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (752 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
tracking-by-detection
multi-vehicle tracking Siamese network data association Markov decision process driving behavior real-time monitoring driver distraction mobile application portable system simulation test dynamic driving behavior traffic scene augmentation corridor model IMU vision classification networks Hough transform lane markings detection semantic segmentation transfer learning autonomous off-road driving tire-road forces estimation slip angle estimation gauge sensors fuzzy logic system load transfer estimation simulation results normalization lateral force empirical model driver monitor lane departure statistical process control fault detection sensor fault signal restoration intelligent vehicle autonomous vehicle kinematic model visual SLAM sparse direct method photometric calibration corner detection and filtering loop closure detection road friction coefficient tire model nonlinear observer self-aligning torque lateral displacement Lyapunov method automatic parking system (APS) end-to-end parking reinforcement learning parking slot tracking deceleration planning multi-layer perceptron smart regenerative braking electric vehicles vehicle speed prediction driver behavior modeling electric vehicle control driver characteristics online learning objects’ edge detection stixel histograms accumulate point cloud segmentation autonomous vehicles scene understanding occlusion reasoning road detection advanced driver assistance system trajectory prediction risk assessment collision warning connected vehicles vehicular communications vulnerable road users fail-operational systems fall-back strategy automated driving advanced driving assistance systems illumination shadow detection shadow edge image processing traffic light detection intelligent transportation system lane-changing merging maneuvers game theory decision-making intelligent vehicles model predictive controller automatic train operation softness factor fusion velocity online obtaining hardware-in-the-loop simulation driving assistant driving diagnosis accident risk maps driving safety intelligent driving virtual test environment millimeter wave radar lane-change decision risk perception mixed traffic minimum safe deceleration automated driving system (ADS) sensor fusion multi-lane detection particle filter self-driving car unscented Kalman filter vehicle model Monte Carlo localization millimeter-wave radar square-root cubature Kalman filter Sage-Husa algorithm target tracking stationary and moving object classification localization LiDAR GNSS Global Positioning System (GPS) monte carlo autonomous driving robot motion path planning piecewise linear approximation multiple-target path planning autonomous mobile robot homotopy based path planning LiDAR signal processing sensor and information fusion advanced driver assistance systems autonomous racing high-speed camera real-time systems LiDAR odometry fail-aware sensors sensing percepction object detection and tracking scene segmentation vehicle positioning fail-x systems driver behavior modelling automatic operation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557112303321 |
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Fernández-Llorca David
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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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Machine Learning Methods with Noisy, Incomplete or Small Datasets
| Machine Learning Methods with Noisy, Incomplete or Small Datasets |
| Autore | Solé-Casals Jordi |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (316 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
open contours
similarly shaped fish species Discrete Cosine Transform (DCT) Discrete Fourier Transform (DFT) Extreme Learning Machines (ELM) feature engineering small data-sets optimization machine learning preprocessing image generation weighted interpolation map binarization single sample per person root canal measurement multifrequency impedance data augmentation neural network functional magnetic resonance imaging independent component analysis deep learning recurrent neural network functional connectivity episodic memory small sample learning feature selection noise elimination space consistency label correlations empirical mode decomposition sparse representations tensor decomposition tensor completion machine translation pairwise evaluation educational data small datasets noisy datasets smart building Internet of Things (IoT) Markov Chain Monte Carlo (MCMC) ontology graph model Artificial Neural Network Discriminant Analysis dengue feature extraction sound event detection non-negative matrix factorization ultrasound images shadow detection shadow estimation auto-encoders semi-supervised learning prediction feature importance feature elimination hierarchical clustering Parkinson’s disease few-shot learning permutation-variable importance topological data analysis persistent entropy support-vector machine data science intelligent decision support social vulnerability gender-gap digital-gap COVID19 policy-making support artificial intelligence imperfect dataset |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557324603321 |
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Solé-Casals Jordi
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Very High Resolution (VHR) Satellite Imagery: Processing and Applications
| Very High Resolution (VHR) Satellite Imagery: Processing and Applications |
| Autore | Marcello Javier |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (262 p.) |
| Soggetto non controllato |
very high-resolution Pléiades imagery
surface convergence data augmentation acquisition geometry SVM classification urban water mapping beaver dam analogue agriculture parcel segmentation morphological building index airborne hypespectral imagery sunglint correction water index over-segmentation index (OSI) High-resolution satellite imagery multi-resolution segmentation (MRS) GaoFen-2 (GF-2) benthic mapping scene classification greenhouse extraction edge constraint Deformable CNN built-up areas extraction ultra-dense connection seagrass beaver mimicry forested mountain natural hazards remote sensing dimensionality reduction techniques road extraction landslide monitoring Slumgullion landslide synthetic aperture radar building detection Worldview-2 saliency index under-segmentation index (USI) texture analysis fast marching method video satellite CNN capsule super-resolution feature distillation shadow detection PrimaryCaps semiautomatic compensation unit superpixels riparian QuickBird submesoscale linear unmixing accuracy assessment composite error index (CEI) cyanobacteria local feature points Faster R-CNN occluded object detection error index of total area (ETA) large displacements threshold stability remote sensing imagery water column correction canopy height model spiral eddy sub-pixel offset tracking consensus stream restoration western Baltic Sea Worldview very high-resolution image CapsNet atmospheric correction |
| ISBN | 3-03921-757-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Very High Resolution |
| Record Nr. | UNINA-9910367747503321 |
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Marcello Javier
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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