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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…
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…
Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection
Xin Wu, Danfeng Hong, Jocelyn Chanussot +3
Geospatial object detection of remote sensing imagery has been attracting an increasing interest in recent years, due to the rapid development in spaceborne imaging. Most of previo…
Cascaded Recurrent Neural Networks for Hyperspectral Image Classification
Renlong Hang, Qingshan Liu, Danfeng Hong +1
By considering the spectral signature as a sequence, recurrent neural networks (RNNs) have been successfully used to learn discriminative features from hyperspectral images (HSIs)…
ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
Xin Wu, Danfeng Hong, Jiaojiao Tian +3
With the rapid development of spaceborne imaging techniques, object detection in optical remote sensing imagery has drawn much attention in recent decades. While many advanced work…