- Tytuł:
- Machine learning versus human-developed algorithms in image analysis of microstructures
- Autorzy:
-
Piwowarczyk, Adam
Wojnar, Leszek - Powiązania:
- https://bibliotekanauki.pl/articles/103967.pdf
- Data publikacji:
- 2019
- Wydawca:
- Stowarzyszenie Menedżerów Jakości i Produkcji
- Tematy:
-
image analysis
object detection
neural networks
machine learning
analiza obrazu
detekcja obiektów
sieci neuronowe
uczenie maszynowe - Opis:
- Automatic image analysis is nowadays a standard method in quality control of metallic materials, especially in grain size, graphite shape and non-metallic content evaluation. Automatically prepared solutions, based on machine learning, constitute an effective and sufficiently precise tool for classification. Human-developed algorithms, on the other hand, require much more experience in preparation, but allow better control of factors affecting the final result. Both attempts were described and compared.
- Źródło:
-
Quality Production Improvement - QPI; 2019, 1, 1; 412-416
2657-8603 - Pojawia się w:
- Quality Production Improvement - QPI
- Dostawca treści:
- Biblioteka Nauki
Artykuł