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Super resolution target identification from remotely sensed images using a Hopfield neural network

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Figure

Fig. 1.Example of Fisher’s argument.
Fig. 2.Hopfield neural network as an analog circuit. The black circles at the intersections represent resistive connections (Ts) between outputs and inputs.Connections between inverted outputs and inputs represent negative connections.
Fig. 3.(a) 2 � 2 pixel image, p and q represent the image dimensions, x and y represent the image pixel coordinates
Fig. 4.Synthetic images and the features of the shapes depicted in each.
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