The study proposed in this paper devises to develop a new methodology based on elliptical basisneural network (EBNN) and on a new feature extraction technique in order to recognize theorganic solar cells (OSCs) defects. The feature extraction procedure has been obtained by usingthe co-occurrence matrices and the SVD decomposition applied to atomic microscope forceimagery. The polymer-based OSCs used for this work have been produced at the optoelectronicorganic semiconductor devices laboratory at Ben Gurion University of the Negev. The testsperformed show that with our approach it is possible to obtain a correct classification percentageof 95.4% proving that the proposed feature extraction technique based on the co-occurrenceMatrix and the SVD decomposition is very effective in the detection of different types of OSC surface defects.
|Titolo:||Organic solar cells defects detection by means of an elliptical basis neural network and a new feature extraction technique|
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||1.1 Articolo in rivista|