Data Science and Knowledge Discovery |
Autore | Portela Filipe |
Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
Descrizione fisica | 1 electronic resource (254 p.) |
Soggetto topico |
Information technology industries
Computer science |
Soggetto non controllato |
crisis reporting
chatbots journalists news media COVID-19 textbook research digital humanities digital infrastructures data analysis content base image retrieval semantic information retrieval deep features multimedia document retrieval data science open government data governance and social institutions economic determinants of open data geoinformation technology fractal dimension territorial road network box-counting framework script Python ArcGIS internet of things LoRaWAN ICT The Things Network ESP32 microcontroller decision systems rule based systems databases rough sets prediction by partial matching spatio-temporal activity recognition smart homes artificial intelligence automation e-commerce machine learning big data customer relationship management (CRM) distracted driving driving behavior driving operation area data augmentation feature extraction authorship text mining attribution neural networks deep learning forensic intelligence dashboard WebGIS data analytics SARS-CoV-2 Big Data Web Intelligence media analytics social sciences humanities linked open data adaptation process interdisciplinary research media criticism classification information systems public health data mining ioCOVID19 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910576878103321 |
Portela Filipe
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Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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Data-Intensive Computing in Smart Microgrids |
Autore | Herodotou Herodotos |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (238 p.) |
Soggetto topico | Technology: general issues |
Soggetto non controllato |
electricity load forecasting
smart grid feature selection Extreme Learning Machine Genetic Algorithm Support Vector Machine Grid Search AMI TL SG NB-PLC fog computing green community resource allocation processing time response time green data center microgrid renewable energy energy trade contract real time power management load forecasting optimization techniques deep learning big data analytics electricity theft detection smart grids electricity consumption electricity thefts smart meter imbalanced data data-intensive smart application cloud computing real-time systems multi-objective energy optimization renewable energy sources wind photovoltaic demand response programs energy management battery energy storage systems demand response scheduling automatic generation control single/multi-area power system intelligent control methods virtual inertial control soft computing control methods |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557603203321 |
Herodotou Herodotos
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Deep Learning Applications with Practical Measured Results in Electronics Industries |
Autore | Kung Hsu-Yang |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica | 1 electronic resource (272 p.) |
Soggetto non controllato |
faster region-based CNN
visual tracking intelligent tire manufacturing eye-tracking device neural networks A* information measure oral evaluation GSA-BP tire quality assessment humidity sensor rigid body kinematics intelligent surveillance residual networks imaging confocal microscope update mechanism multiple linear regression geometric errors correction data partition Imaging Confocal Microscope image inpainting lateral stage errors dot grid target K-means clustering unsupervised learning recommender system underground mines digital shearography optimization techniques saliency information gated recurrent unit multivariate time series forecasting multivariate temporal convolutional network foreign object data fusion update occasion generative adversarial network CNN compressed sensing background model image compression supervised learning geometric errors UAV nonlinear optimization reinforcement learning convolutional network neuro-fuzzy systems deep learning image restoration neural audio caption hyperspectral image classification neighborhood noise reduction GA MCM uncertainty evaluation binary classification content reconstruction kinematic modelling long short-term memory transfer learning network layer contribution instance segmentation smart grid unmanned aerial vehicle forecasting trajectory planning discrete wavelet transform machine learning computational intelligence tire bubble defects offshore wind multiple constraints human computer interaction Least Squares method |
ISBN | 3-03928-864-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910404080403321 |
Kung Hsu-Yang
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MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Deep Learning for Facial Informatics |
Autore | Hsu Gee-Sern Jison |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica | 1 electronic resource (102 p.) |
Soggetto topico | History of engineering & technology |
Soggetto non controllato |
deep learning
RGB depth facial landmarking merging networks 3D geometry data 2D attribute maps fused CNN feature coarse-to-fine convolutional neural network (CNN) deep metric learning multi-task learning image classification age estimation generative adversarial network emotion classification facial key point detection facial images processing convolutional neural networks face liveness detection convolutional neural network thermal image external knowledge |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557721303321 |
Hsu Gee-Sern Jison
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Deep Learning for Toxicity and Disease Prediction |
Autore | Gong Ping |
Pubbl/distr/stampa | Frontiers Media SA, 2020 |
Descrizione fisica | 1 electronic resource (143 p.) |
Soggetto topico |
Science: general issues
Medical genetics |
Soggetto non controllato |
deep learning
disease diagnosis or prognosis chemical toxicity prediction deep neural networks conventional machine learning |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557407303321 |
Gong Ping
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Frontiers Media SA, 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Deep Learning in Aging Neuroscience |
Autore | Ramírez Javier |
Pubbl/distr/stampa | Frontiers Media SA, 2020 |
Descrizione fisica | 1 electronic resource (127 pages) |
Soggetto topico |
Science: general issues
Neurosciences |
Soggetto non controllato |
deep learning
convolutional neural networks brain age estimation neurodegenerative diseases automated diagnosis brain image segmentation |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557586903321 |
Ramírez Javier
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Frontiers Media SA, 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Deep Learning in Medical Image Analysis |
Autore | Zhang Yudong |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (458 p.) |
Soggetto non controllato |
interpretable/explainable machine learning
image classification image processing machine learning models white box black box cancer prediction deep learning multimodal learning convolutional neural networks autism fMRI texture analysis melanoma glcm matrix machine learning classifiers explainability explainable AI XAI medical imaging diagnosis ARMD change detection unsupervised learning microwave breast imaging image reconstruction tumor detection digital pathology whole slide image processing multiple instance learning deep learning classification HER2 medical images transfer learning optimizers neo-adjuvant treatment tumour cellularity cancer breast cancer diagnostics imaging computation artificial intelligence 3D segmentation active surface discriminant analysis PET imaging medical image analysis brain tumor cervical cancer colon cancer lung cancer computer vision musculoskeletal images lung disease detection taxonomy convolutional neural network CycleGAN data augmentation dermoscopic images domain transfer macroscopic images skin lesion segmentation infection detection COVID-19 X-ray images bayesian inference shifted-scaled dirichlet distribution MCMC gibbs sampling object detection surgical tools open surgery egocentric camera computers in medicine segmentation MRI ECG signal detection portable monitoring devices 1D-convolutional neural network medical image segmentation domain adaptation meta-learning U-Net computed tomography (CT) magnetic resonance imaging (MRI) low-dose sparse-angle quantitative comparison |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557435103321 |
Zhang Yudong
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Deep Learning-Based Action Recognition |
Autore | Lee Hyo Jong |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
Descrizione fisica | 1 electronic resource (240 p.) |
Soggetto topico |
Technology: general issues
History of engineering & technology |
Soggetto non controllato |
human action recognition
graph convolution high-order feature spatio-temporal feature feature fusion dynamic gesture recognition multi-modalities network class regularization 3D-CNN spatiotemporal activations class-specific features Dynamic Hand Gesture Recognition human-computer interaction hand shape features pose estimation stacked hourglass network deep learning convolutional receptive field hand gesture recognition human-machine interface artificial intelligence feedforward neural networks spatio-temporal image formation human activity recognition fusion strategies transfer learning activity recognition data augmentation multi-person pose estimation partitioned centerpose network partition pose representation continuous hand gesture recognition gesture spotting gesture classification multi-modal features 3D skeletal CNN spatiotemporal feature embedded system real-time action recognition Long Short-Term Memory spatio-temporal differential |
ISBN | 3-0365-5200-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910619465803321 |
Lee Hyo Jong
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MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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Development of Unconventional Reservoirs 2020 |
Autore | Rezaee Reza |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (748 p.) |
Soggetto topico |
Research & information: general
Technology: general issues |
Soggetto non controllato |
bedding fractures
failure criterion lamina tight oil tight sandstone finite element simulation numerical simulation unconventional reservoir permeability group method of data handling artificial neural network well logs sensitivity analysis tight gas reservoir multi-fractured horizontal well (MFHW) unstable productivity model productivity forecast influencing factor analysis horizontal well with multiple finite-conductivity fractures elliptical-shaped drainage productivity index non-Darcy flow pressure-dependent conductivity reservoir properties void space structure porosity complex rocks NMR MICP CT SEM coal-bearing tight sandstone organic-rich clasts occurrence classifications formation mechanisms Ordos Basin hydraulic fracturing fracturing fluids fluids-rock interaction environmental implication history matching semianalytic model unconventional gas reservoirs multistage fractured horizontal wells fractal theory pore structure heterogeneity NMR measurements multifractal analysis shale reservoir elastic properties brittleness rock physics brittle spot identification shale gas reservoir characteristics gas content eastern Sichuan Basin the Da’anzhai member pulse decay method gas adsorption dual media unconventional core natural fracture influencing factor oil production carbonate rock basement reservoir Jizhong Sub-basin dynamic pore network modeling shale reservoirs water imbibition discrete element method modified fluid-mechanical coupling algorithm injection sequence well spacing stress shadow effect seismic location microseismic events waveform stacking induced seismicity CBM surfactant solid-free drilling fluid CBM reservoir wettability machine learning lithofacies umiat Alaska proppant transportation cross fractures CFD simulation dimensional analysis equilibrium proppant height coalbed methane Lattice Boltzmann method gas diffusion adsorption–desorption pore-scale clay minerals pore structures tight gas reservoirs Xujiaweizi Rift Northern Songliao Basin methane adsorption isotherm coal properties gradient boosting decision tree estimation model shale gas reservoir geology Gibbs excess adsorption supercritical adsorption gas viscosity high voltage spark discharge electrohydraulic effect electrical conductivity drilling rock damage pressure waves water fracturing turbulence effect Eulerian multiphase modeling proppant transport mechanism equilibrium height prediction model adaptive filtering complex noise canceling electromagnetic telemetry multifractured horizontal wells production analysis irregular stimulated region natural gas hydrate seismic modeling fractional derivatives gas geochemical characteristics noble gas shale gas evolution Large Igneous Province (LIP) gas loss geological structure gas controlling pattern neutral surface tectonic movement Bumu region seismic interpretation depositional environments characteristics Wheeler diagram seismic attributes heterogeneous sequence sample size neutron scattering mercury injection capillary pressure adsorption shale junggar basin hong-che fault zone carboniferous volcanic reservoir main controlling factors of hydrocarbon accumulation fracture vug micro CT carbonate wave velocity amorphous SiO2 X-ray diffraction X-ray fluorescence spectrometry scanning electron microscope quantitative analysis void ratio FEM ABAQUS matrix porosity kerogen porosity water saturation gas hydrate saturation deep learning recurrent neural network molecular simulation enhanced oil recovery methane shale petroleum technological development patent network analysis imbibition osmosis unconventional formations EOR water flooding |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557332603321 |
Rezaee Reza
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Diagnosis of neurogenetic disorders : contribution of next generation sequencing and deep phenotyping / / special issue editor, Alisdair McNeill |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (94 p.) |
Disciplina | 612.8 |
Soggetto topico | Neurogenetics |
Soggetto non controllato |
polymicrogyria
neurodegenerative disease next generation sequencing (NGS) inborn error of metabolism genetic biomarker deep learning TUBA1A Alzheimer's disease (AD) ataxia risk prediction p.(Arg2His) movement science tubulin R2H diagnosis machine learning metal storage disorders amyotrophic lateral sclerosis (ALS) glucocerebrosidase Parkinsonism cerebellar hypoplasia Gaucher disease disease phenotyping tubulinopathy Parkinson's disease (PD) dementia Parkinson's disease |
ISBN | 3-03921-611-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Altri titoli varianti | Diagnosis of Neurogenetic Disorders |
Record Nr. | UNINA-9910367751303321 |
MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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