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Innovative Topologies and Algorithms for Neural Networks
| Innovative Topologies and Algorithms for Neural Networks |
| Autore | Xibilia Maria Gabriella |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (198 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
3D convolution neural network
action recognition alternative fusion neural network Arabic named entity recognition attention mechanism autoencoders bidirectional gated recurrent unit bidirectional recurrent neural network Chinese text classification CNN convolution neural Networks convolutional neural network convolutional neural networks deep convolutional neural networks deep learning distributed systems elements recognition embedded deep learning facial image analysis facial nerve paralysis feature fusion fully convolutional network fused features gesture recognition gradient-weighted class activation maps graph convolutional network graph partitioning GRU human computer interaction image classification Internet of Things IoT (Internet of Thing) systems linguistic features long short-term memory long short-term-memory long-short-term memory networks LSTM LSTM-CRF model medical applications motion map multi-label learning natural language processing object detection network object recognition pedestrian attribute recognition POS syntactic rules resource-efficient inference scalability sentiment analysis sentiment attention mechanism ship identification text recognition tooth-marked tongue word embedding |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557553903321 |
Xibilia Maria Gabriella
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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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Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (414 pages) |
| Soggetto topico | Computer science |
| 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 |
9783038976851
3038976857 |
| 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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Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang |
| 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 |
9783038976998
3038976997 |
| 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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Remote Sensing Data Compression
| Remote Sensing Data Compression |
| Autore | Lukin Vladimir |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (366 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
3D-CALIC
CCSDS CCSDS 123.0-B-2 compact data structure complexity compressed sensing compression impact compressive sensing computational complexity coupled dictionary crop classification DACs data compression EBCOT Elias codes FAPEC FPGA fully convolutional network GPU graph filterbanks graph signal processing group convolution HEVC high bit-depth compression hyperspectral hyperspectral image hyperspectral image coding hyperspectral images hyperspectral imaging hyperspectral scenes image classification image quality integer-to-integer transforms intra coding invertible projection JPEG 2000 JPEG2000 k2-raster k2-tree Landsat-8 learned compression lossless compression lossy compression M-CALIC multispectral multispectral image compression multispectral satellite images near-lossless hyperspectral image compression neural networks on board compression on-board compression on-board data compression on-board processing parallel computing partitioned extraction PCA PForDelta quadtree rate-distortion real time real-time compression real-time performance real-time transmission remote sensing remote sensing data compression Rice codes semantic segmentation Sentinel-2 Simple16 Simple9 singular value spectral image spectral-spatial feature synthetic aperture sonar task-driven learning tensor decomposition transform transform coding UAV UAVs underwater sonar imaging variational autoencoder visual quality metrics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557383103321 |
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Lukin Vladimir
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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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Remote Sensing of the Oceans : Blue Economy and Marine Pollution
| Remote Sensing of the Oceans : Blue Economy and Marine Pollution |
| Autore | Buono Andrea |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (224 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
accumulation-rate
adaptive joint time-frequency (AJTF) decomposition airborne HF/VHF radar AMD anthropogenic-marine-debris azimuth autocorrelation function beached-marine-litter BML co-evolutionary particle swarm optimization convolutional neural networks counter-flow eddy detection algorithms fully convolutional network general compact polarimetry geometric active contour model HF radar hybrid dual-polarization ideal test Kuroshio intrusion low-backscattering areas marine economy marine raft aquaculture marine-economic effects marine-pollution marine-protected-areas mathematical model moving vessel MPA multicomponent polynomial phase signal(mc-PPS) n/a nonsubsampled contourlet transform Northern East China Sea (NECS) ocean environment ocean modeling oil spill oil spill discrimination ortho-photo polarimetric decomposition radar cross section SAR SAR images sea echo semantic segmentation sentinel-1 Sentinel-1 shoreline extraction storm surge superpixel surface currents Synthetic Aperture Radar synthetic aperture radar (SAR) target decomposition tropical cyclone size (TC size) UAVs unmanned-aerial-vehicles vertical migration |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Remote Sensing of the Oceans |
| Record Nr. | UNINA-9910557667403321 |
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Buono Andrea
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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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