IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
... (for ESS/CS/ES/ISS)
Tech. Rep. Archives
... (for ES/CS)
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2018-05-14 11:50
SAVERS: SAR ATR with Verification Support Based on Convolutional Neural Network
Hidetoshi Furukawa
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a new convolutional neural network (CNN) which performs coarse and fine segmentation for end-to-end synthetic aperture radar (SAR) automatic target recognition (ATR) system. In recent years, many CNNs for SAR ATR using deep learning have been proposed, but most of them classify target classes from fixed size target chips extracted from SAR imagery. On the other hand, we proposed the CNN which outputs the score of the multiple target classes and a background class for each pixel from the SAR imagery of arbitrary size and multiple targets as fine segmentation. However, it was necessary for humans to judge the CNN segmentation result. In this report, we propose a CNN called SAR ATR with verification support (SAVERS), which performs region-wise (i.e. coarse) segmentation and pixel-wise segmentation. SAVERS discriminates between target and non-target, and classifies multiple target classes and non-target class by coarse segmentation. This report describes the evaluation results of SAVERS using the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset.
Keyword (in Japanese) (See Japanese page) 
(in English) automatic target recognition (ATR) / multiple targets / detection / discrimination / classification / convolutional neural network (CNN) / deep learning / synthetic aperture radar (SAR)  
Reference Info. IEICE Tech. Rep., vol. 118, no. 28, SANE2018-5, pp. 23-28, May 2018.
Paper # SANE2018-5 
Date of Issue 2018-05-07 (SANE) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380

Conference Information
Committee SANE  
Conference Date 2018-05-14 - 2018-05-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Kikai-Shinko-Kaikan Bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Radar, EW and general 
Paper Information
Registration To SANE 
Conference Code 2018-05-SANE 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) SAVERS: SAR ATR with Verification Support Based on Convolutional Neural Network 
Sub Title (in English)  
Keyword(1) automatic target recognition (ATR)  
Keyword(2) multiple targets  
Keyword(3) detection  
Keyword(4) discrimination  
Keyword(5) classification  
Keyword(6) convolutional neural network (CNN)  
Keyword(7) deep learning  
Keyword(8) synthetic aperture radar (SAR)  
1st Author's Name Hidetoshi Furukawa  
1st Author's Affiliation * (*)
2nd Author's Name  
2nd Author's Affiliation ()
3rd Author's Name  
3rd Author's Affiliation ()
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker
Date Time 2018-05-14 11:50:00 
Presentation Time 25 
Registration for SANE 
Paper # IEICE-SANE2018-5 
Volume (vol) IEICE-118 
Number (no) no.28 
Page pp.23-28 
#Pages IEICE-6 
Date of Issue IEICE-SANE-2018-05-07 


[Return to Top Page]

[Return to IEICE Web Page]


The Institute of Electronics, Information and Communication Engineers (IEICE), Japan