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As the most commonly techniques to landslide inventory mapping, visual interpretation and geomorphological field surveys are time-consuming and labor-intensive. In this paper, a probabilistic topic model, maximum entropy discrimination latent Dirichlet allocation (MedLDA), is presented to detect landslides with satellite images of two different spatial resolutions in a weakly supervised way. A two-stage...
Probabilistic topic models have has successfully been used to classify remote sensing images in unsupervised way. However, the relationship among pixels is ignored in these applications because of the assuption of “bag of words”. This assuption leads to “pepper and salt effect” when these models are used to classify Very High Resolution (VHR) remote sensing images. To solve this problem, a novel model...
A novel model is presented to address the problem of semantic clustering of geo-objects in very high resolution panchromatic satellite images. The proposed model combines a probabilistic topic model with a multiscale image representation into an automatic framework by embedding both document and scale selections. The probabilistic topic model is used to characterize the statistical distributions of...
The spacecraft TT&C resources scheduling (STRS) studies the problem of how to allocating the tracking, telemetry and command (TT&C) resources reasonably and satisfying the various requests of different spacecrafts for TT&C services. This article analyzes the spacecraft TT&C requirements and determines the crucial objects and procedures of STRS activities. The constraints and rules...
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