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In this paper, a new All-Convolutional Networks (A-ConvNets) is proposed and applied to Moving and Stationary Target Acquisition and Recognition (MSTAR) data. Conventional deep learning algorithms, especially the deep convolutional networks (ConvNets) have achieved many success state-of-art results. However, directly applying ConvNets to SAR data will yield severe overfitting because of limited data...
In this work, we consider the accuracy improvement of the high frequency scattered fields from the 3-D convex scatterers with the aid of the Fock current and the incremental length diffraction coefficient (ILDC) technique. To efficiently calculate the Fock currents, we adopt the numerical contour deformation method. Then, by using the Fock currents and the ILDC technique, high frequency scattered...
In this paper, the high-frequency diffracted waves like the creeping waves are comprehensively analyzed by the Fock currents. On invoking the contour deformation method, the highly oscillatory Fock currents are efficiently calculated. Furthermore, the workload for the calculation of Fock currents is frequency-independent. To capture the high-frequency wave physics phenomenon, the Fock current is separated...
In this paper, interferometric synthetic aperture radar (InSAR) data are utilized to extract the forestry damage information caused by typhoon over Tomakomai, Hokkaido, Japan. By computing the interferograms of two single-pass X-band SAR data before and after the typhoon, the change of their heights could be detected even the fallen tress were not cleared, and therefore, the damage level can then...
Relevance feedback is an iterative search technique to bridge the semantic gap between the high level user intention and low level data representation. This technique interactively determines a user's desired output or query concept by asking the user whether certain proposed 3D models are relevant or not. For a relevance feedback algorithm to be effective, it must grasp a user's query concept accurately...
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