Neural networks for HREM image analysis
We present a new neural network-based method of image processing for determining the local composition and thickness of IIIV semiconductors in high resolution electron microscope images. This is of great practical interest as these parameters influence the electrical properties of the semiconductor. Neural networks suppress correlated noise from amorphous object covering and distinguish between variations of sample thickness and semiconductor composition.
neural network image processing electron microscopy compound semiconductor