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Advanced Techniques for Ground Penetrating Radar Imaging
| Advanced Techniques for Ground Penetrating Radar Imaging |
| Autore | López Yuri |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (218 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
Ground Penetrating Radar (GPR)
Unmanned Aerial Vehicles (UAVs) Synthetic Aperture Radar (SAR) Real Time Kinematic (RTK) Ultra-Wide-Band (UWB) landmine and IED detection non-destructive testing GPR coherence semblance attribute analysis imaging GPR trace high-resolution data large-scale survey archaeological prospection Ground-Penetrating Radar velocity analysis coherency functionals GPR data processing GPR data migration spatial-variant convolution neural network (SV-CNN) spatial-variant convolution kernel (SV-CK) radar image enhancing MIMO radar neural networks imaging radar ground penetrating radar wavelet scattering network machine learning support vector machine pipeline identification snow snow water equivalent (SWE) stepped-frequency continuous wave radar (SFCW) software defined radio (SDR) snowpack multilayer reflectance Ground Penetrating Radar Synthetic Aperture Radar landmine Improvised Explosive Device radar noise attenuation Gaussian spike impulse noise deep convolutional denoising autoencoders (CDAEs) deep convolutional denoising autoencoders with network structure optimization (CDAEsNSO) applied geophysics digital signal processing enhancement of 3D-GPR datasets clutter noise removal spectral filtering ground-penetrating radar nondestructive testing pipelines detection modeling signal processing |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557337403321 |
López Yuri
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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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Advances in Computational Intelligence Applications in the Mining Industry
| Advances in Computational Intelligence Applications in the Mining Industry |
| Autore | Ganguli Rajive |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (324 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
truck dispatching
mining equipment uncertainties orebody uncertainty discrete event simulation Q-learning grinding circuits minerals processing random forest decision trees machine learning knowledge discovery variable importance mineral prospectivity mapping random forest algorithm epithermal gold unstructured data blast impact empirical model mining fragmentation mine worker fatigue random forest model health and safety management stockpiles operational data mine-to-mill geostatistics ore control mine optimization digital twin modes of operation geological uncertainty multivariate statistics partial least squares regression oil sands bitumen extraction bitumen processability mine safety and health accidents narratives natural language processing random forest classification hyperspectral imaging multispectral imaging dimensionality reduction neighbourhood component analysis artificial intelligence mining exploitation masonry buildings damage risk analysis Bayesian network Naive Bayes Bayesian Network Structure Learning (BNSL) rock type mining geology bluetooth beacon classification and regression tree gaussian naïve bayes k-nearest neighbors support vector machine transport route transport time underground mine tactical geometallurgy data analytics in mining ball mill throughput measurement while drilling non-additivity coal petrographic analysis macerals image analysis semantic segmentation convolutional neural networks point cloud scaling fragmentation size analysis structure from motion |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557613103321 |
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Ganguli Rajive
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Image Processing, Analysis and Recognition Technology
| Advances in Image Processing, Analysis and Recognition Technology |
| Autore | Frejlichowski Dariusz |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (386 p.) |
| Soggetto topico |
Information technology industries
Computer science |
| Soggetto non controllato |
CIELab
component Substitution Pan sharpening Pléiades VHR Image coal inertinite macerals classification multifractal analysis support vector machine block-based coding video coding H.265/HEVC affine motion compensation image registration homography matrix local homography transformation convolutional neural network moving direct linear transformation super-resolution (SR) convolution neural network (CNN) Gene Expression Programming (GEP) deep learning image preclassification suspicious behavior detection motion magnitude gradient reactivity saliency haze removal dark channel atmospheric-light estimation coarse-to-fine search strategy sparse dictionary stable recovery frame RIP local dimming retinex theory bi-histogram equalization contrast ratio details preservation pansharpening image fusion image quality Satellite Pour l'Observation de la Terre (SPOT) 6 spectral consistency spatial consistency synthesis artificial intelligence dental application images detection parseval frame transform sparse representation octave convolution bilingual scene text reading Ethiopic script attention nasal cytology automatic cell segmentation rhinology image analysis feature extraction shape context plant recognition DPCNN BOF numeral spotting historical document analysis convolutional neural networks deep transfer learning handwritten digit recognition spectrum correction intensity correction compressed sensing tradeoff process IKONOS remote sensing fine-tuning learning rate scheduler cyclical learning rates label smoothing classification accuracy neural networks salient object detection RGB-D object detection small object multi-scale sampling balanced sampling texture structure optical coke iron ore sinter image processing segmentation identification action recognition silhouette sequences shape features ambient assisted living active ageing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576879103321 |
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Frejlichowski Dariusz
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Near Infrared Spectroscopy and Related Computational Methods
| Advances in Near Infrared Spectroscopy and Related Computational Methods |
| Autore | Bec Krzysztof B |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (496 p.) |
| Soggetto non controllato |
pocket-sized spectrometer
standard germination tests total hydroxycinnamic derivatives hyperspectral image quantitative analysis modeling tissue chemotherapy FTIR spectroscopy cheese biomeasurements chemometrics affine invariance rapid identification biodiagnosis bioanalytical applications fat NIRS pixel-wise paraffin-embedded late preterm maize kernel photonics hyperspectral image processing image processing colorectal cancer test set validation deep convolutional neural network near-infrared fluorescence classification variety discrimination near-infrared hyperspectral imaging ensemble learning light origin traceability Paris polyphylla var. yunnanensis Fourier transform mid-infrared spectroscopy dry matter Fourier transform infrared spectroscopy hyperspectral imaging FT-NIR spectroscopy proximal sensing perfusion measurements near-infrared spectroscopy stained carotenoids cellular imaging perturbation direct model transferability clinical classifications counterfeit and substandard pharmaceuticals hyperspectral imaging technology spectral imaging SVM nutritional parameters extra virgin olive oil ethanol osteopathy living cells object-wise water-mirror approach Chrysanthemum bootstrapping soft shrinkage FTIR PLS-R multivariate data analysis combination bands binary dragonfly algorithm geographical origin Vitis vinifera L. glucose detection di-(2-picolyl)amine non-destructive sensor splanchnic adulteration animal origin melamine artemether MicroNIR™ brain fluorescent probes Folin-Ciocalteu SCiO support vector machine anharmonic quantum mechanical calculations PLSR Zn(II) RMSEP overtones blackberries pasta/sauce blends FT-IR partial least squares calibration partial least squares (PLS) auxiliary diagnosis handheld near-infrared spectroscopy precision viticulture partial least squares seeds vitality freeze-damaged near infrared discriminant analysis corn seed quantum chemical calculation anharmonic calculation Trichosanthis Fructus moisture analytical spectroscopy Raman spectroscopy NIR spectroscopy calibration transfer imaging water lumefantrine BRAF V600E mutation wavelength selection bone cancer imaging visualization near infrared spectroscopy raisins chemometric techniques data fusion prepared slices Ewing sarcoma biomonitoring Rubus fructicosus VIS/NIR hyperspectral imaging combinations bands quantitative analysis model partial least square regression DFT calculations TreeBagger antimalarial tablets accelerated aging agriculture crude drugs spectroscopy rice seeds PLS isotopic substitution multivariate calibration phytoextraction Fourier-transform near-infrared spectroscopy phenolics deparaffinized near-infrared (NIR) spectroscopy SIMCA counter propagation artificial neural network fructose PLS-DA ultra-high performance liquid chromatography aquaphotomics support vector machine-discriminant analysis hier-SVM DNA NIR support vector machine model API principal component analysis |
| ISBN | 3-03928-053-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910372786503321 |
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Bec Krzysztof B
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Remote Sensing for Global Forest Monitoring
| Advances in Remote Sensing for Global Forest Monitoring |
| Autore | Tomppo Erkki |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (352 p.) |
| Soggetto topico |
Research & information: general
Environmental economics |
| Soggetto non controllato |
forest structure change
EBLUP small area estimation multitemporal LiDAR and stand-level estimates forest cover Sentinel-1 Sentinel-2 data fusion machine-learning Germany South Africa temperate forest savanna classification Sentinel 2 land use land cover improved k-NN logistic regression random forest support vector machine statistical estimator IPCC good practice guidelines activity data emissions factor removals factor Picea crassifolia Kom compatible equation nonlinear seemingly unrelated regression error-in-variable modeling leave-one-out cross-validation digital surface model digital terrain model canopy height model constrained neighbor interpolation ordinary neighbor interpolation point cloud density stereo imagery remotely sensed LAI field measured LAI validation magnitude uncertainty temporal dynamics state space models forest disturbance mapping near real-time monitoring CUSUM NRT monitoring deforestation degradation tropical forest tropical peat forest type deep learning FCN8s CRFasRNN GF2 dual-FCN8s random forests error propagation bootstrapping Landsat LiDAR La Rioja forest area change data assessment uncertainty evaluation inconsistency forest monitoring drought time series satellite data Bowen ratio carbon flux boreal forest windstorm damage synthetic aperture radar C-band genetic algorithm multinomial logistic regression |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557338103321 |
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Tomppo Erkki
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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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AI and Financial Markets
| AI and Financial Markets |
| Autore | Hamori Shigeyuki |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (230 p.) |
| Soggetto topico | Economics, finance, business & management |
| Soggetto non controllato |
algorithmic trading
Stop Loss Turtle ATR community finances fiscal flexibility individualized financial arrangements sustainable financial services price momentum hidden markov model asset allocation blockchain BlockCloud Artificial Intelligence consensus algorithms exchange rates fundamentals prediction random forest support vector machine neural network deep reinforcement learning financial market simulation agent based simulation artificial market simulation CAR regulation portfolio contract for difference CfD reinforcement learning RL neural networks long short-term memory LSTM Q-learning deep learning uncertainty economic policy text mining topic model yield curve term structure of interest rates machine learning autoencoder interpretability |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557584903321 |
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Hamori Shigeyuki
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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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Artificial Intelligence for Smart and Sustainable Energy Systems and Applications
| Artificial Intelligence for Smart and Sustainable Energy Systems and Applications |
| Autore | Lytras Miltiadis |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (258 p.) |
| Soggetto non controllato |
artificial neural network
home energy management systems conditional random fields LR ELR energy disaggregation artificial intelligence genetic algorithm decision tree static young’s modulus price scheduling self-adaptive differential evolution algorithm Marsh funnel energy yield point non-intrusive load monitoring mud rheology distributed genetic algorithm MCP39F511 Jetson TX2 sustainable development artificial neural networks transient signature load disaggregation smart villages ambient assisted living smart cities demand side management smart city CNN wireless sensor networks object detection drill-in fluid ERELM sandstone reservoirs RPN deep learning RELM smart grids multiple kernel learning load feature extraction NILM energy management energy efficient coverage insulator Faster R-CNN home energy management smart grid LSTM smart metering optimization algorithms forecasting plastic viscosity machine learning computational intelligence policy making support vector machine internet of things sensor network nonintrusive load monitoring demand response |
| ISBN | 3-03928-890-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404078103321 |
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Lytras Miltiadis
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 |
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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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Corporate Bankruptcy Prediction : International Trends and Local Experience
| Corporate Bankruptcy Prediction : International Trends and Local Experience |
| Autore | Prusak Błażej |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (202 p.) |
| Soggetto topico | Economics, finance, business & management |
| Soggetto non controllato |
ISA 701
audit expectation gap key audit matters materiality Poland corporate bankruptcy forecasting fuzzy sets artificial neural networks decision trees bankruptcy prediction tax arrears payment defaults financial ratios failure bankruptcy chapter 11 regression count meta-analysis literature review manufacturing insolvency prediction citation mining classification credit risk modelling corporate failure rating systems ensemble classifiers boosting bagging stacking scoring models insolvency financial distress default forecasting methods models predicting financial distress phases of economic cycle Czech Republic European large companies bankruptcy risk company performance Principal Component Analysis neural networks support vector machine bankruptcy model |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Corporate Bankruptcy Prediction |
| Record Nr. | UNINA-9910557527203321 |
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Prusak Błażej
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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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Emerging Sensor Technology in Agriculture
| Emerging Sensor Technology in Agriculture |
| Autore | Fuentes Sigfredo |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (240 p.) |
| Soggetto topico |
Research & information: general
Geography |
| Soggetto non controllato |
apple orchards
modeling and simulation unmanned aerial vehicles fruit ripeness ethylene gas detection 3D crop modeling remote sensing on-ground sensing depth images parameter acquisition capacitor sensor deposit mass pesticide droplets formulations ionization CFD airflow field test monitoring method spectral sensor crop growth computer vision deep learning image processing pose estimation animal detection precision livestock Citrus sinensis L. Osbeck mechanical harvesting acceleration sensor vibration time logistic regression adaptive thresholding fruit detection parameter tuning phenotype phenotyping phenomics Triticum aestivum water deficit stress infrared leaf area index cocoa beans volatile compounds artificial neural networks VitiCanopy app bushfires infrared thermography near-infrared spectroscopy smoke taint artificial intelligence Kinect sensor RGB RGB-D image segmentation colour thresholding bunch area bunch volume point cloud mesh surface reconstruction image analysis cluster morphology machine learning non-invasive sensing technologies proximal sensing precision viticulture partial least square support vector machine Gaussian processes soybean pigeon pea guar tepary bean |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557295003321 |
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Fuentes Sigfredo
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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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