- Tytuł:
- Learning-free deep features for multispectral palm-print classification
- Autorzy:
-
Aounallah, Asma
Meraoumia, Abdallah
Bendjenna, Hakim - Powiązania:
- https://bibliotekanauki.pl/articles/27312870.pdf
- Data publikacji:
- 2023
- Wydawca:
- Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
- Tematy:
-
feature extraction
biometrics
multispectral imaging
deep learning
DCTNet
data fusion - Opis:
- The feature-extraction step is a major and crucial step in analyzing and understanding raw data, as it has a considerable impact on system accuracy. Despite the very acceptable results that have been obtained by many handcrafted methods, these can unfortunately have difficulty representing features in the cases of large databases or with strongly correlated samples. In this context, we attempt to examine the discriminability of texture features by proposing a novel, simple, and lightweight method for deep feature extraction to characterize the discriminative power of different textures. We evaluated the performance of our method by using a palm print-based biometric system, and the experimental results (using the CASIA multispectral palm--print database) demonstrate the superiority of the proposed method over the latest handcrafted and deep methods.
- Źródło:
-
Computer Science; 2023, 24 (2); 243--271
1508-2806
2300-7036 - Pojawia się w:
- Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł