Name
Abstract | ||
|---|---|---|
We have addressed the problem of analyzing images containing multiple sparse overlapped patterns. This problem arises naturally when analyzing the composition of organic macro- molecules using data gathered from their NMR spectra. Using a neural network approach, we have obtained excellent results in using NMR data to analyze the presence of various amino acids in protein molecules. We have achieved high correct classification percentages (about 87%) for images containing as many as five sub stantially distorted overlapping patterns. |
Year | DOI | Venue |
|---|---|---|
1991 | 10.1016/0031-3203(93)90026-S | Pattern Recognition |
Keywords | Field | DocType |
protein molecule,neural network approach,analyzing image,nmr data,organic macromolecule,multiple sparse pattern,high correct classification percentage,excellent result,nmr spectrum,various amino acid,overlapping pattern,multiple sparse overlapped pattern,data gathering,neural network,amino acid | Pattern recognition,Computer science,NMR spectra database,Protein molecules,Artificial intelligence,Artificial neural network,Cluster analysis,Machine learning | Conference |
Volume | Issue | ISSN |
26 | 11 | 0031-3203 |
ISBN | Citations | PageRank |
1-55860-160-0 | 6 | 0.76 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rangachari Anand | 1 | 24 | 4.71 |
| Kishan Mehrotra | 2 | 325 | 38.97 |
| Chilukuri K. Mohan | 3 | 595 | 65.03 |
| Sanjay Ranka | 4 | 2017 | 303.99 |