TY - GEN
T1 - Deep Rule-Based Aerial Scene Classifier using High-Level Ensemble Feature Descriptor
AU - Gu, Xiaowei
AU - Angelov, Plamen Parvanov
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9/30
Y1 - 2019/9/30
N2 - In this paper, a new deep rule-based approach using high-level ensemble feature descriptor is proposed for aerial scene classification. By creating an ensemble of three pre-trained deep convolutional neural networks for feature extraction, the proposed approach is able to extract more discriminative representations from the local regions of aerial images. With a set of massively parallel IF...THEN rules built upon the prototypes identified through a self-organizing, nonparametric, transparent and highly human-interpretable learning process, the proposed approach is able to produce the state-of-the-art classification results on the unlabeled images outperforming the alternatives. Numerical examples on benchmark datasets demonstrate the strong performance of the proposed approach.
AB - In this paper, a new deep rule-based approach using high-level ensemble feature descriptor is proposed for aerial scene classification. By creating an ensemble of three pre-trained deep convolutional neural networks for feature extraction, the proposed approach is able to extract more discriminative representations from the local regions of aerial images. With a set of massively parallel IF...THEN rules built upon the prototypes identified through a self-organizing, nonparametric, transparent and highly human-interpretable learning process, the proposed approach is able to produce the state-of-the-art classification results on the unlabeled images outperforming the alternatives. Numerical examples on benchmark datasets demonstrate the strong performance of the proposed approach.
KW - aerial scene classification
KW - deep convolutional neural network
KW - deep rule-based
KW - ensemble feature descriptor
UR - http://www.research.lancs.ac.uk/portal/en/publications/deep-rulebased-aerial-scene-classifier-using-highlevel-ensemble-feature-descriptor(bd168f1f-22d7-4cb8-be96-e6851aebb258).html
UR - http://www.scopus.com/inward/record.url?scp=85073225835&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2019.8851838
DO - 10.1109/IJCNN.2019.8851838
M3 - Conference Proceeding (Non-Journal item)
SN - 9781728119861
T3 - Proceedings of the International Joint Conference on Neural Networks
BT - 2019 International Joint Conference on Neural Networks (IJCNN)
PB - IEEE Press
ER -