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Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification
Danfeng Hong, Xin Wu, Pedram Ghamisi +3
Up to the present, an enormous number of advanced techniques have been developed to enhance and extract the spatially semantic information in hyperspectral image processing and ana…
Learning Shared Cross-modality Representation Using Multispectral-LiDAR and Hyperspectral Data
Danfeng Hong, Jocelyn Chanussot, Naoto Yokoya +2
Due to the ever-growing diversity of the data source, multi-modality feature learning has attracted more and more attention. However, most of these methods are designed by jointly…
Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
Yuxing Xie, Jiaojiao Tian, Xiao Xiang Zhu
3D Point Cloud Semantic Segmentation (PCSS) is attracting increasing interest, due to its applicability in remote sensing, computer vision and robotics, and due to the new possibil…
Relation Network for Multi-label Aerial Image Classification
Yuansheng Hua, Lichao Mou, Xiao Xiang Zhu
Multi-label classification plays a momentous role in perceiving intricate contents of an aerial image and triggers several related studies over the last years. However, most of the…
SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion
Michael Schmitt, Lloyd Haydn Hughes, Chunping Qiu +1
The availability of curated large-scale training data is a crucial factor for the development of well-generalizing deep learning methods for the extraction of geoinformation from m…
MIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data
Jingliang Hu, Danfeng Hong, Xiao Xiang Zhu
Multi-modal data fusion has recently been shown promise in classification tasks in remote sensing. Optical data and radar data, two important yet intrinsically different data sourc…
Fusion of Heterogeneous Earth Observation Data for the Classification of Local Climate Zones
Guichen Zhang, Pedram Ghamisi, Xiao Xiang Zhu
This paper proposes a novel framework for fusing multi-temporal, multispectral satellite images and OpenStreetMap (OSM) data for the classification of local climate zones (LCZs). F…
A Relation-Augmented Fully Convolutional Network for Semantic Segmentation in Aerial Scenes
Lichao Mou, Yuansheng Hua, Xiao Xiang Zhu
Most current semantic segmentation approaches fall back on deep convolutional neural networks (CNNs). However, their use of convolution operations with local receptive fields cause…
Learnable Manifold Alignment (LeMA) : A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification
Danfeng Hong, Naoto Yokoya, Nan Ge +2
In this paper, we aim at tackling a general but interesting cross-modality feature learning question in remote sensing community --- can a limited amount of highly-discrimin-ative…
Potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection
Michael Schmitt, Gerald Baier, Xiao Xiang Zhu
This article investigates the potential of nonlocally filtered pursuit monostatic TanDEM-X data for coastline detection in comparison to conventional TanDEM-X data, i.e. image pair…