@inproceedings{e60dbe0ce96544089e4c222e413cf375,
title = "Region Based Ensemble Learning Network for Fine-Grained Classification",
abstract = "As an important research topic in computer vision, fine-grained classification which aims to recognition subordinate-level categories has attracted significant attention. We propose a novel region based ensemble learning network for fine-grained classification. Our approach contains a detection module and a module for classification. The detection module is based on the faster R-CNN framework to locate semantic regions of the object. The classification module using an ensemble learning method, trains a set of sub-classifiers for different semantic regions and combines them together to get a stronger classifier. In the evaluation, we implement experiments on the CUB-2011 dataset and the result of experiments proves our method is efficient for fine-grained classification. We also extend our approach to remote scene recognition and evaluate it on the NWPU-RESISC45 dataset.",
keywords = "Ensemble learning, Fine-grained classification, Region detection, Remote sensing image",
author = "Weikuang Li and Tian Wang and Mengyi Zhang and Chuanyun Wang and Guangcun Shan and Hichem Snoussi",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 Chinese Automation Congress, CAC 2018 ; Conference date: 30-11-2018 Through 02-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/CAC.2018.8623687",
language = "英语",
series = "Proceedings 2018 Chinese Automation Congress, CAC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4173--4177",
booktitle = "Proceedings 2018 Chinese Automation Congress, CAC 2018",
address = "美国",
}