- Tytuł:
- Face Recognition Comparative Analysis Using Different Machine Learning Approaches
- Autorzy:
-
Ahmed, Nisar
Khan, Farhan Ajmal
Ullah, Zain
Ahmed, Hasnain
Shahzad, Taimur
Ali, Nableela - Powiązania:
- https://bibliotekanauki.pl/articles/2024199.pdf
- Data publikacji:
- 2021
- Wydawca:
- Stowarzyszenie Inżynierów i Techników Mechaników Polskich
- Tematy:
-
linear discriminant analysis
k-nearest neighbor
support vector machine
principal component analysis
liniowa analiza dyskryminacyjna
maszyna wektorów podporowych
analiza głównych składowych - Opis:
- The problem of a facial biometrics system was discussed in this research, in which different classifiers were used within the framework of face recognition. Different similarity measures exist to solve the performance of facial recognition problems. Here, four machine learning approaches were considered, namely, K-nearest neighbor (KNN), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Principal Component Analysis (PCA). The usefulness of multiple classification systems was also seen and evaluated in terms of their ability to correctly classify a face. A combination of multiple algorithms such as PCA+1NN, LDA+1NN, PCA+ LDA+1NN, SVM, and SVM+PCA was used. All of them performed with exceptional values of above 90% but PCA+LDA+1N scored the highest average accuracy, i.e. 98%.
- Źródło:
-
Advances in Science and Technology. Research Journal; 2021, 15, 1; 265-272
2299-8624 - Pojawia się w:
- Advances in Science and Technology. Research Journal
- Dostawca treści:
- Biblioteka Nauki
Artykuł