Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4962553 | Procedia Technology | 2016 | 6 Pages |
Abstract
Identification and classification of the topographical features is a challenging topic in the field of image pattern recognition. Improvement is required in the existing crater detection algorithms because of the pattern types and complexity. Currently more than 500 images are transmitted to earth with a resolution of 5 to 100 meters. The artificial neural network plays an important role in training and classification of image patterns. This paper deals with analysis of crater detection with back propagation algorithm with training and classification, and analysis of execution time for classification of craters.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
R. Krishnan, Andhe Dharani,