Image Classification Using Ensemble Algorithms with Deep Learning and Hand-Crafted Features
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, ensemble learning based image classification method is proposed by using both features extracted by means of pre-trained convolutional neural networks (CNN) and hand-crafted. Recently, deep learning models have been widely used in computer vision applications and significantly increase performance. in this scope, classification process is performed by adding 4 hand-crafted features to 4096 deep learning features on the CIFAR-10 dataset. The contribution to the performance of system is measured by using both hand-crafted and deep learning features together. Classification accuracy rate is used as the performance criterion. Experimental studies show that the developed method gives better results than only using the deep learning features.
Açıklama
26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY
Anahtar Kelimeler
deep learning, CNN, ensemble learning, feature extraction, image processing, machine learning, classification
Kaynak
2018 26Th Signal Processing and Communications Applications Conference (Siu)
WoS Q Değeri
N/A
