Analyzing images containing multiple sparse patterns with neural networks

摘要

The problem of analyzing images containing multiple sparse overlapped patterns is addressed. This problem arises naturally when analyzing the composition of organic macromolecules using data gathered from their NMR spectra. Using a neural network approach, excellent results are obtained in using NMR data to analyze the presence of various amino acids in protein molecules. High correct classification percentages (about 87%) are achieved for images containing as many as five substantially distorted overlapping patterns.