ICA neural net to refine remote sensing with multiple labels

We show how the unsupervised ANN modeling of image fusion of HVS can embody the mathematics of ICA to achieve blind source de-mixing of remote sensing images. We have shown when tow eyes are extended to multiple pixel has a large footprint on the ground. MLRS gives the percentage composition of ground radiation sources within the footprint and thus overcome the so-called 'boundary error' coined by Tucker in the Amazon deforestation over-estimation as follows.

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