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A Deep Rule-based Approach for Satellite Scene Image Analysis

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date7/10/2018
Host publication2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
PublisherIEEE
Pages2778-2783
Number of pages6
ISBN (electronic)9781538666500
ISBN (print)9781538666517
<mark>Original language</mark>English
EventIEEE SMC 2018 conference - Miyazaki, Japan
Duration: 7/10/2018 → …
http://www.smc2018.org/

Conference

ConferenceIEEE SMC 2018 conference
Country/TerritoryJapan
CityMiyazaki
Period7/10/18 → …
Internet address

Publication series

Name2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
PublisherIEEE
ISSN (Print)1062-922X
ISSN (electronic)2577-1655

Conference

ConferenceIEEE SMC 2018 conference
Country/TerritoryJapan
CityMiyazaki
Period7/10/18 → …
Internet address

Abstract

Satellite scene images contain multiple sub-regions of different land use categories; however, traditional approaches usually classify them into a particular category only. In this paper, a new approach is proposed for automatically analyzing the semantic content of sub-regions of satellite images. At the core of the proposed approach is the recently introduced deep rule-based image classification method. The proposed approach includes a self-organizing set of transparent zero order fuzzy IF-THEN rules with human-interpretable prototypes identified from the training images and a pre-trained deep convolutional neural network as the feature descriptor. It requires a very short, nonparametric, highly parallelizable training process and can perform a highly accurate analysis on the semantic features of local areas of the image with the generated IF-THEN rules in a fully automatic way. Examples based on benchmark datasets demonstrate the validity and effectiveness of the proposed approach.

Bibliographic note

©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.