- Tytuł:
- Object classification with artificial neural networks : A comparative analysis
- Autorzy:
-
Domeradzki, Kornel
Niewiadomski, Artur - Powiązania:
- https://bibliotekanauki.pl/articles/1819259.pdf
- Data publikacji:
- 2019
- Wydawca:
- Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
- Tematy:
-
object classification
neural networks
convolutional neural networks
residual neural networks - Opis:
- Object classification is a problem which has attracted a lot of research attention in recent years. Traditional approach to this problem is built on a shallow trainable architecture that was meant to detect handcrafted features. That approach works poorly and introduces many complications in situations where one is to work with more than a couple types of objects in an image with a large resolution. That is why in the past few years convolutional and residual neural networks have experienced a tremendous rise in popularity. In this paper, we provide a review on topics related to artificial neural networks and a brief overview of our research. Our review begins with a short introduction to the topic of computer vision. Afterwards we cover briefly the concepts of neural networks, convolutional and residual neural networks and their commonly used models. Then we provide a comparative performance analysis of the previously mentioned models in a binary and multi-label classification problem. Finally, multiple conclusions are drawn, which are to serve as guidelines for future computer vision systems implementations.
- Źródło:
-
Studia Informatica : systems and information technology; 2019, 1-2(23); 43--56
1731-2264 - Pojawia się w:
- Studia Informatica : systems and information technology
- Dostawca treści:
- Biblioteka Nauki
Artykuł