| dc.contributor.author | Budak, Ü. |  | 
| dc.contributor.author | Şengür, A. |  | 
| dc.contributor.author | Guo, Y. |  | 
| dc.contributor.author | Akbulut, Y. |  | 
| dc.contributor.author | Vespa, L.J. |  | 
| dc.date.accessioned | 2021-12-16T10:12:14Z |  | 
| dc.date.available | 2021-12-16T10:12:14Z |  | 
| dc.date.issued | 2017 |  | 
| dc.identifier.isbn | 9.78154E+12 |  | 
| dc.identifier.uri | https://doi.org/10.1109/IDAP.2017.8090215 |  | 
| dc.identifier.uri | http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/13068 |  | 
| dc.description.abstract | Interpretting color fundus images by doctors is enhanced by computer-aided detection (CAD). Microaneurysm (MA) detection in CAD is an important step to identify the retinal diseases automatically. However, MA detection is still a challenging task due to t |  | 
| dc.language.iso | English |  | 
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. |  | 
| dc.relation.ispartof | 2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 |  | 
| dc.source | IDAP 2017 - International Artificial Intelligence and Data Processing Symposium |  | 
| dc.title | A novel approach based on image processing algorithms for microaneurysm candidate detection |  | 
| dc.type | Conference Paper |  | 
| dc.identifier.doi | 10.1109/IDAP.2017.8090215 |  | 
| dc.identifier.scopus | 2-s2.0-85039911921 |  |