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The multisensory fusion of remote sensing data has obtained a great attention in recent years. In this letter, we propose a new feature fusion framework based on deep neural networks (DNNs). The proposed framework employs deep convolutional neural networks (CNNs) to effectively extract features of multi-/hyper-spectral and light detection and ranging (LiDAR) data. Then, a fully connected DNN is designed to fuse the heterogeneous features obtained by the previous CNNs. Through the aforementioneddoi:10.1109/lgrs.2017.2704625 fatcat:bmplmahdureynasabirdfavz24