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http://localhost:8080/xmlui/handle/123456789/147548| Title: | Neoplasm |
| Authors: | Hafiz Naveed Shahzad |
| Issue Date: | 2018 |
| Publisher: | IntechOpen |
| link: | https://www.intechopen.com/books/neoplasm |
| Keywords: | Neoplasms. Tumors. Oncology;hyperspectral image classification;SELF;SVMs;Segment-Tree Filtering;multi-sensor;change feature analysis;object-based;multispectral images;heterogeneous domain adaptation;transfer learning;multi-view canonical correlation analysis ensemble;semi-supervised learning;canonical correlation weighted voting;ensemble learning;image classification;spatial attraction model (SAM);subpixel mapping (SPM);land cover;mixed pixel;spatial distribution;hard classification;building damage detection;Fuzzy-GA decision making system;machine learning techniques;optical remotely sensed images;sensitivity analysis;texture analysis;quality assessment;ratio images;Synthetic Aperture Radar (SAR);speckle;speckle filters;ice concentration;SAR imagery;convolutional neural network;urban surface water extraction;threshold stability;sub-pixel;linear spectral unmixing;Landsat imagery;image registration;image fusion;UAV;metadata;visible light and infrared integrated camera;semantic segmentation;CNN;deep learning;ISPRS;remote sensing;gate;hyperspectral image;sparse and low-rank graph;tensor;dimensionality reduction;semantic labeling;convolution neural network;fully convolutional network;sea-land segmentation;ship detection;hyperspectral image;target detection;multi-task learning;sparse representation;locality information;remote sensing image correction;color matching;optimal transport;CNN;very high resolution images;segmentation;multi-scale clustering;vehicle localization;vehicle classification;high resolution;aerial image;convolutional neural network (CNN);class imbalance;deep learning;convolutional neural network (CNN);fully convolutional network (FCN);classification;remote sensing;high resolution;semantic segmentation;deep convolutional neural networks;manifold ranking;single stream optimization;high resolution image;feature extraction;hypergraph learning;morphological profiles;hyperedge weight estimation;semantic labeling;convolutional neural networks;remote sensing;deep learning;aerial images;hyperspectral image;feature extraction;dimensionality reduction;optimized kernel minimum noise fraction (OKMNF);hyperspectral remote sensing;endmember extraction;multi-objective;particle swarm optimization;image alignment;feature matching;geostationary satellite remote sensing image;GSHHG database;Hough transform;dictionary learning;road detection;Radon transform;geo-referencing;multi-sensor image matching;Siamese neural network;satellite images;synthetic aperture radar;inundation mapping;flood;optical sensors;spatiotemporal context learning;Modest AdaBoost;HJ-1A/B CCD;GF-4 PMS;hyperspectral image classification;automatic cluster number determination;adaptive convolutional kernels;hyperspectral imagery;1-dimensional (1-D);Convolutional Neural Network (CNN);Support Vector Machine (SVM);Random Forests (RF);machine learning;deep learning;TensorFlow;multi-seasonal;regional land cover;saliency analysis;remote sensing;ROI detection;hyperparameter sparse representation;dictionary learning;energy distribution optimizing;multispectral imagery;nonlinear classification;kernel method;dimensionality expansion;deep convolutional neural networks;road segmentation;conditional random fields;satellite images;aerial images;THEOS;land cover change;downscaling;sub-pixel change detection;machine learning;MODIS;Landsat;very high resolution (VHR) satellite image;topic modelling;object-based image analysis;image segmentation;unsupervised classification;multiscale representation;GeoEye-1;wavelet transform;fuzzy neural network;remote sensing;conservation;urban heat island;land surface temperature;climate change;land use;land cover;Landsat;remote sensing;SAR image;despeckling;dilated convolution;skip connection;residual learning;scene classification;saliency detection;deep salient feature;anti-noise transfer network;DSFATN;infrared image;image registration;MSER;phase congruency;hashing;remote sensing image retrieval;online learning;hyperspectral image;compressive sensing;structured sparsity;tensor sparse decomposition;tensor low-rank approximation |
| ISBN: | 9781789237771 9781789237788 |
| Theme: | 教科書-醫學類 |
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