| dc.creator |
Ortac, Gizem |
|
| dc.creator |
TAŞDEMİR, KADİM |
|
| dc.creator |
Durmus, Efkan |
|
| dc.creator |
Bilgi, Ahmet Seckin |
|
| dc.creator |
Kalkan, Habil |
|
| dc.date |
2015-01-01T01:00:00Z |
|
| dc.date.accessioned |
2021-12-03T11:19:58Z |
|
| dc.date.available |
2021-12-03T11:19:58Z |
|
| dc.identifier |
34ec1e8e-1d73-4a53-b918-4bd2d7332577 |
|
| dc.identifier |
10.1109/siu.2015.7129942 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/34ec1e8e-1d73-4a53-b918-4bd2d7332577/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/90847 |
|
| dc.description |
Turkey is the major producer of fig fruit and is the biggest dried fig exporter in the World. However, aflatoxin and mold related effects degrade the figs quality and make them inappropriate for human consumption. Aspergillus niger is one of these molds that degrades the quality and turns the color of figs into black. The figs infected by A. niger need to be eliminated from the sound figs before consumption. Traditionally, these figs are detected by manually testing each fig sample. However, manual testing is labor intensive and includes the risk of spreading the molds to the sound samples. In this study, a hyperspectral imaging and classification system is proposed to detect the A. Niger infected figs by non-destructive approach. The infected figs are detected by 100% accuracy by the proposed method. |
|
| dc.language |
tur |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
An Automated System For Detecting the Infected Figs by Hyperspectral Image Analysis |
|
| dc.type |
info:eu-repo/semantics/conferenceObject |
|