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Label Relation Inference for Multi-Label Aerial Image Classification

Hua, Yuansheng and Mou, LiChao and Zhu, Xiao Xiang (2019) Label Relation Inference for Multi-Label Aerial Image Classification. In: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, pp. 5244-5247. IGARSS 2019, 28.7.-2. Aug. 2019, Yokohama, Japan. DOI: 10.1109/IGARSS.2019.8898934

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Official URL: https://ieeexplore.ieee.org/document/8898934

Abstract

Multi-label aerial image classification is a challenging visual task and obtaining increasing attention recently. Most of the existing methods resort to training independent classifier for each label, while underlying label correlations are not fully exploited while making predictions. To this end, we propose an innovative inference network, which takes advantage of pairwise label relations to infer multiple object labels of a high-resolution aerial image. Specifically, we first employ a feature extraction module to extract high-level feature representations of an aerial image, and then, feed them into a relational inference module to predict the presence of each object label. We evaluate our network on the UCM multilabel dataset and experiment with various popular convolutional neural networks (CNNs) as the backbone of the feature extraction module. Experimental results demonstrate that the proposed network behaves superiorly in comparison with other existing methods.

Item URL in elib:https://elib.dlr.de/134105/
Document Type:Conference or Workshop Item (Speech)
Title:Label Relation Inference for Multi-Label Aerial Image Classification
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hua, YuanshengYuansheng.Hua (at) dlr.deUNSPECIFIED
Mou, LiChaoLiChao.Mou (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:August 2019
Journal or Publication Title:IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2019.8898934
Page Range:pp. 5244-5247
Status:Published
Keywords:label relation, relational inference network, multi-label classification, CNN
Event Title:IGARSS 2019
Event Location:Yokohama, Japan
Event Type:international Conference
Event Dates:28.7.-2. Aug. 2019
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Haschberger, Dr.-Ing. Peter
Deposited On:13 Feb 2020 10:08
Last Modified:13 Feb 2020 10:08

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