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Convolutional Neural Network (CNN) is achieving remarkable progress in various computer vision tasks. In the past few years, the remote sensing community has observed Deep Neural Network (DNN) finally taking off in several challenging fields. In this study, we propose a DNN to generate a predefined High Resolution (HR) synthetic spectral band using...
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Context 1
... F RB,n (.) denotes the operations of n th residual block inside the LRFE unit. The number of channels present in the internal layers of a residual block is represented by feature size in Section IV-C-Table III. As shown in Fig. 5, the residual block used in DeepSWIR is a slight variant of the original residual block with skip connections [18] in a sense that it does not use activation units at the output and is expected to adaptively capture the dynamic range of radiometric values. Hence, the output of F RB,n (.) is computed by fusing the global features F GF ...
Context 2
... F RB,n (.) denotes the operations of n th residual block inside the LRFE unit. The number of channels present in the internal layers of a residual block is represented by feature size in Section IV-C-Table III. As shown in Fig. 5, the residual block used in DeepSWIR is a slight variant of the original residual block with skip connections [18] in a sense that it does not use activation units at the output and is expected to adaptively capture the dynamic range of radiometric values. Hence, the output of F RB,n (.) is computed by fusing the global features F GF ...
Context 3
... F RB,n (.) denotes the operations of n th residual block inside the LRFE unit. The number of channels present in the internal layers of a residual block is represented by feature size in Section IV-C-Table III. As shown in Fig. 5, the residual block used in DeepSWIR is a slight variant of the original residual block with skip connections [18] in a sense that it does not use activation units at the output and is expected to adaptively capture the dynamic range of radiometric values. Hence, the output of F RB,n (.) is computed by fusing the global features F GF ...
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Traditional Neural Networks (NN) have been popular in the satellite remote sensing community for the last 25 years. For coarse resolution infrared or microwave instruments, NN algorithms have been used at the pixel level. New neural architectures such as Convolutional Neural Networks (CNN) use the Deep Learning (DL) approach to solve complex proble...
