Automated Detection of Insect-Damaged Sunflower Seeds by X-Ray Imaging
Year
: 2014DOI: 10.13031/aea.30.9942
Keyword(s): Classification, Morphology, Rapid, Single seed.
Collections
:
-
Statistics
Automated Detection of Insect-Damaged Sunflower Seeds by X-Ray Imaging
Show full item record
| date accessioned | 2020-03-11T13:15:59Z | |
| date available | 2020-03-11T13:15:59Z | |
| date issued | 2014 | |
| identifier issn | 0883-8542 | |
| identifier other | 10.13031-aea.30.9942.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/537584?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | American Society of Agricultural & Biological Engineers | |
| title | Automated Detection of Insect-Damaged Sunflower Seeds by X-Ray Imaging | |
| type | Journal Paper | |
| contenttype | Metadata Only | |
| identifier padid | 4296698 | |
| subject keywords | Classification, Morphology, Rapid, Single seed. | |
| identifier doi | 10.13031/aea.30.9942 | |
| journal title | Applied Engineering in Agriculture | |
| journal volume | 30 | |
| journal issue | 1 | |
| filesize | 994233 | |
| citations | 0 | |
| contributor rawauthor | Tom C. Pearson, Jarrad Prasifka, Dan Brabec, Ron Haff, Brent Hulke |