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Tag Archive 'deep learning'

Our feature paper “Hyperspectral and LiDAR Fusion Using Deep Three-Stream Convolutional Neural Networks” is now published online.
Recently, convolutional neural networks (CNN) have been intensively investigated for the classification of remote sensing data by extracting invariant and abstract features suitable for classification. In this paper, a novel framework is proposed for the fusion of hyperspectral images [...]

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Our paper about Deep Learning from Multiple Crowds: A Case Study of Humanitarian Mapping is available online now.
Satellite images are widely applied in humanitarian mapping which labels buildings, roads and so on for humanitarian aid and economic development. However, the labeling now is mostly done by volunteers. In a recently accepted study, we utilize deep learning [...]

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Satellite images are widely applied in humanitarian mapping which labels buildings, roads and so on for humanitarian aid and economic development. However, the labeling now is mostly done by volunteers. In a recently accepted study, we utilize deep learning to solve humanitarian mapping tasks of a mobile software named MapSwipe. The current deep learning techniques [...]

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Recently, deep learning has been widely applied in pattern recognition with satellite images. Deep learning techniques like Convolutional Neural Network and Deep Belief Network have shown outstanding performance in detecting ground objects like buildings and roads, and the learnt deep features are further applied in some prediction tasks like poverty and population mapping. On the [...]

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Last week (Sept. 18-22, 2017), our six colleagues, Prof. Alexander Zipf, Doctoral Candidate Xuke Hu, Dr. Hongchao Fan, Dr. Martin Hämmerle, Dr. Zhiyong Wang, and Dr. Wei Huang, participated in the ISPRS Geospatial Week 2017 held in Wuhan, China.

In the opening ceremony on Sept. 18, 2017, the U.V. Helava Award was presented to [...]

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