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ISPRS Journal of Photogrammetry and Remote Sensing Vol.158 December 2019

Derek Lichti - Personal Name;

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


Availability
M.4153-XII-2019526.982Perpustakaan BIG (500)Available
Detail Information
Series Title
-
Call Number
526.982
Publisher
Amsterdam : Elsevier., 2019
Collation
317 hlm.; ilus 28cm.
Language
Inggris
ISBN/ISSN
0924-2716
Classification
526.982
Content Type
text
Media Type
other
Carrier Type
unspecified
Edition
Vol.158
Subject(s)
Penginderaan Jauh
Specific Detail Info
-
Statement of Responsibility
Editor-in-Chief Derek Lichti
Other version/related

No other version available

File Attachment
  • 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☆
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