PERPUSTAKAAN BIG

1.Application of convolutional neural networks for low vegetation filtering from data acquired by UAVs p.1-10
2.Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture p.11-22
3.Improving the estimation of fractional vegetation cover from UAV RGB imagery by colour unmixing p.23-34
4.Learning to propagate labels on graphs: An iterative multitask regression framework for semi-supervised hyperspectral dimensionality reduction p.35-49
5.An implicit radar convolutional burn index for burnt area mapping with Sentinel-1 C-band SAR data p.50-62
6.Multi-modal deep learning for landform recognition p.63.75
7.Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests p.76-89
8.Quantifying PM2.5 mass concentration and particle radius using satellite data and an optical-mass conversion algorithm p.90-98
9.A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction p.99-112
10.On the value of corner reflectors and surface models in InSAR precise point positioning p.113-122
11.NRLI-UAV: Non-rigid registration of sequential raw laser scans and images for low-cost UAV LiDAR point cloud quality improvement p.123-145
12.Plenoptic camera calibration based on microlens distortion modelling p.146-154
13.Spatial information inference net: Road extraction using road-specific contextual information p.155-166
14.Metaheuristic pansharpening based on symbiotic organisms search optimization p.167-187
15.Estimation and analysis of along-track attitude jitter of ZiYuan-3 satellite based on relative residuals of tri-band multispectral imagery p.188-200
16.Using spectral Geodesic and spatial Euclidean weights of neighbourhood pixels for hyperspectral Endmember Extraction preprocessing p.201-218
17.Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees p.219-230
18.Statistical retrieval of atmospheric profiles with deep convolutional neural networks p.231-240
19.Matching of TerraSAR-X derived ground control points to optical image patches using deep learning p.241-248
20.A time-series classification approach based on change detection for rapid land cover mapping☆ p.249-262
21.Predicting forest fires burned area and rate of spread from pre-fire multispectral satellite measurements p.263-278
22.Deep learning classifiers for hyperspectral imaging: A review p.279-317

M.4153-XII-2019

526.982

Perpustakaan BIG (500)

Tersedia

• Application of convolutional neural networks for low vegetation filtering from data acquired by UAVs
• Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture
• Improving the estimation of fractional vegetation cover from UAV RGB imagery by colour unmixing
• Learning to propagate labels on graphs: An iterative multitask regression framework for semi-supervised hyperspectral dimensionality reduction
• An implicit radar convolutional burn index for burnt area mapping with Sentinel-1 C-band SAR data
• Multi-modal deep learning for landform recognition
• Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests
• Quantifying PM2.5 mass concentration and particle radius using satellite data and an optical-mass conversion algorithm
• A comprehensive evaluation of disturbance agent classification approaches: Strengths of ensemble classification, multiple indices, spatio-temporal variables, and direct prediction
• On the value of corner reflectors and surface models in InSAR precise point positioning
• NRLI-UAV: Non-rigid registration of sequential raw laser scans and images for low-cost UAV LiDAR point cloud quality improvement
• Plenoptic camera calibration based on microlens distortion modelling
• Spatial information inference net: Road extraction using road-specific contextual information
• Metaheuristic pansharpening based on symbiotic organisms search optimization
• Estimation and analysis of along-track attitude jitter of ZiYuan-3 satellite based on relative residuals of tri-band multispectral imagery
• Using spectral Geodesic and spatial Euclidean weights of neighbourhood pixels for hyperspectral Endmember Extraction preprocessing
• Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees
• Statistical retrieval of atmospheric profiles with deep convolutional neural networks
• Matching of TerraSAR-X derived ground control points to optical image patches using deep learning
• A time-series classification approach based on change detection for rapid land cover mapping☆

Share :