| 000 | 01678naaaa2200337uu 4500 | ||
|---|---|---|---|
| 001 | https://directory.doabooks.org/handle/20.500.12854/61453 | ||
| 005 | 20220219215135.0 | ||
| 020 | _aKSP/1000085620 | ||
| 020 | _a9783731508427 | ||
| 024 | 7 |
_a10.5445/KSP/1000085620 _cdoi |
|
| 041 | 0 | _aGerman | |
| 042 | _adc | ||
| 100 | 1 |
_aRichter, Matthias _4auth |
|
| 245 | 1 | 0 | _aÜber lernende optische Inspektion am Beispiel der Schüttgutsortierung |
| 260 |
_bKIT Scientific Publishing _c2018 |
||
| 300 | _a1 electronic resource (XVI, 283 p. p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aAutomated visual inspection is an integral part in industrial manufacturing processes, but development and setup of such systems is very costly. Machine learning significantly reduces the effort of and speeds up both tasks. This work develops several machine learning methods suitable for automated visual inspection. The methods augment each other and can be used for a wide range of products. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by-sa/4.0/ _2cc _4https://creativecommons.org/licenses/by-sa/4.0/ |
||
| 546 | _aGerman | ||
| 653 | _aMustererkennung | ||
| 653 | _aSchüttgutsortierung | ||
| 653 | _avisual inspection | ||
| 653 | _aoptische Inspektion | ||
| 653 | _amaschinelles Lernen | ||
| 653 | _aPattern recognition | ||
| 653 | _amachine learning | ||
| 653 | _abulk material soriting | ||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://www.ksp.kit.edu/9783731508427 _70 _zDOAB: download the publication |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/61453 _70 _zDOAB: description of the publication |
| 999 |
_c46103 _d46103 |
||