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Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
| Advances in Artificial Intelligence: Models, Optimization, and Machine Learning |
| Autore | Leon Florin |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (362 p.) |
| Soggetto topico |
Research & information: general
Mathematics & science |
| Soggetto non controllato |
large margin nearest neighbor regression
distance metrics prototypes evolutionary algorithm approximate differential optimization multiple point hill climbing adaptive sampling free radical polymerization autonomous driving object tracking trajectory prediction deep neural networks stochastic methods applied machine learning classification and regression data mining ensemble model engineering informatics gender-based violence in Mexico twitter messages class imbalance k-nearest neighbor instance-based learning graph neural network deep learning hyperparameters machine learning optimization inference metaheuristics animal-inspired exploration exploitation hot rolled strip steel surface defects defect classification knockout tournament dynamic programming algorithm computational complexity combinatorics intelligent transport systems traffic control spatial-temporal variable speed limit multi-agent systems reinforcement learning distributed W-learning urban motorways multi-agent framework NET framework simulations agent-based systems agent algorithms software design multisensory fingerprint interoperability DeepFKTNet classification generative adversarial networks image classification transfer learning plastic bottle |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Advances in Artificial Intelligence |
| Record Nr. | UNINA-9910580212403321 |
Leon Florin
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Hyperspectral Imaging and Applications
| Hyperspectral Imaging and Applications |
| Autore | Chang Chein-I |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (632 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
biodiversity
peatland vegetation type classification hyperspectral in situ measurements hyperspectral image (HSI) multiscale union regions adaptive sparse representation (MURASR) multiscale spatial information imaging spectroscopy airborne laser scanning minimum noise fraction class imbalance Africa agroforestry tree species hyperspectral unmixing endmember extraction band selection spectral variability prototype space ensemble learning rotation forest semi-supervised local discriminant analysis optical spectral region thermal infrared spectral region mineral mapping data integration HyMap AHS raw material remote sensing nonnegative matrix factorization data-guided constraints sparseness evenness hashing ensemble hierarchical feature hyperspectral classification band expansion process (BEP) constrained energy minimization (CEM) correlation band expansion process (CBEP) iterative CEM (ICEM) nonlinear band expansion (NBE) Otsu’s method sparse unmixing local abundance nuclear norm hyperspectral detection target detection sprout detection constrained energy minimization iterative algorithm adaptive window hyperspectral imagery recursive anomaly detection local summation RX detector (LS-RXD) sliding window band selection (BS) band subset selection (BSS) hyperspectral image classification linearly constrained minimum variance (LCMV) successive LCMV-BSS (SC LCMV-BSS) sequential LCMV-BSS (SQ LCMV-BSS) vicarious calibration reflectance-based method irradiance-based method Dunhuang site 90° yaw imaging terrestrial hyperspectral imaging vineyard water stress machine learning tree-based ensemble progressive sample processing (PSP) real-time processing image fusion hyperspectral image panchromatic image structure tensor image enhancement weighted fusion spectral mixture analysis fire severity AVIRIS deep belief networks deep learning texture feature enhancement band grouping hyperspectral compression lossy compression on-board compression orthogonal projections Gram–Schmidt orthogonalization parallel processing anomaly detection sparse coding KSVD hyperspectral images (HSIs) SVM composite kernel algebraic multigrid methods hyperspectral pansharpening panchromatic intrinsic image decomposition weighted least squares filter spectral-spatial classification label propagation superpixel semi-supervised learning rolling guidance filtering (RGF) graph deep pipelined background statistics high-level synthesis data fusion data unmixing hyperspectral imaging |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910585941603321 |
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Chang Chein-I
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images . Volume 2
| Learning to Understand Remote Sensing Images . Volume 2 |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (363 pages) |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN | 3-03897-699-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755503321 |
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Wang Qi
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images . Volume 1
| Learning to Understand Remote Sensing Images . Volume 1 |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (414 pages) |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN | 3-03897-685-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755603321 |
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Wang Qi
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Systems Analytics and Integration of Big Omics Data
| Systems Analytics and Integration of Big Omics Data |
| Autore | Hardiman Gary |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (202 p.) |
| Soggetto non controllato |
precision medicine informatics
drug sensitivity chromatin modification cell lines biocuration neurodegeneration multivariate analysis artificial intelligence epigenetics missing data sequencing clinical data class imbalance integrative analytics algorithm development for network integration deep phenotype non-omics data feature selection Gene Ontology miRNA-gene expression networks omics data plot visualization Alzheimer's disease tissue classification epidemiological data proteomic analysis genotype RNA expression indirect effect multi-omics dementia multiomics integration data integration phenomics network topology analysis challenges transcriptome enrichment analysis regulatory genomics scalability heterogeneous data systemic lupus erythematosus database microtubule-associated protein tau disease variants genomics joint modeling distance correlation annotation phenotype direct effect curse of dimensionality gene-environment interactions logic forest machine learning KEGG pathways multivariate causal mediation amyloid-beta bioinformatics pipelines support vector machine pharmacogenomics candidate genes tissue-specific expressed genes cognitive impairment causal inference |
| ISBN | 3-03928-745-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910404089603321 |
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Hardiman Gary
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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