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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
AP 2023-05-12
15:30
Okinawa Okinawa Gender Equality Center
(Primary: On-site, Secondary: Online)
On Classification Accuracy Improvement of Polarimetric Scattering Component Decomposition for PolSAR data
Hiroyoshi Yamada, Masato Kawada, Ryoichi Sato (Niigata Univ.) AP2023-23
In polarimetric SAR (PolSAR) data analysis, one of popular techniques to extract target features is methods of polarimet... [more] AP2023-23
pp.80-85
SANE, SAT
(Joint)
2023-03-03
13:10
Okinawa
(Primary: On-site, Secondary: Online)
On Polarimetric Scattering Component Decomposition for PolSAR image by Using Random-rotated Dihedral Scattering Component
Hiroyoshi yamada, Yuta Suzuki, Masato Kawada, Ryoichi Sato (Niigata Univ.) SANE2022-118
In polarimetry, SAR image classification, PolSAR, model-based scattering sower decomposition which decomposes data into ... [more] SANE2022-118
pp.107-112
SANE 2022-12-16
11:45
Nagasaki Nagasaki Public Hall
(Primary: On-site, Secondary: Online)
General 5-component Scattering Power Decomposition with Unitary Transformation
Yoshio Yamaguchi (Niigata Univ.), Gulab Singh (IITB, India), Ryu Sugimoto (AIST) SANE2022-80
Polarimetric synthetic aperture radar (PolSAR) provides us with a full 3x3 coherency matrix that bears 9 real-valued and... [more] SANE2022-80
pp.85-90
SANE 2022-12-16
13:55
Nagasaki Nagasaki Public Hall
(Primary: On-site, Secondary: Online)
Study on Volume Scattering Model in Scattering Power Decomposition for PolSAR Data
Masato Kawada, Hiroyoshi Yamada, Ryoichi Sato (Niigata Univ.) SANE2022-82
The main objective of this paper is to improve the classification accuracy of PolSAR data for urban areas. In the PolSAR... [more] SANE2022-82
pp.95-99
EMT, IEE-EMT 2022-11-17
09:35
Tokyo Kikai-Shinko-Kaikan Bldg.
(Primary: On-site, Secondary: Online)
A RFI detection method in SAR using the complex amplitude information of dual polarization
Akira Uozumi, Akira Hirose, Ryo Natsuaki (UT) EMT2022-52
We propose a method to detect radio frequency interference (RFI) superimposed on synthetic aperture radar (SAR) images u... [more] EMT2022-52
pp.47-52
AP 2022-10-19
09:30
Gifu GIFU CITY CULTURE CENTER
(Primary: On-site, Secondary: Online)
[Poster Presentation] Fundamental Study on Improvement of Misclassification of Urban Areas in Scattering Power Decomposition for PolSAR Data
Masato Kawada, Hiroyoshi Yamada, Ryoichi Sato (Niigata Univ.) AP2022-108
Recently, classification of ground surfaces using Polarimetric Synthetic Aperture Radar (PolSAR) data has been expected ... [more] AP2022-108
pp.65-69
AP, SANE, SAT
(Joint)
2022-07-27
12:40
Hokkaido Asahikawa Taisetsu Crystal Hall
(Primary: On-site, Secondary: Online)
Fundamental Study on Misclassification of Urban Areas in Scattering Power Decomposition for PolSAR Data
Yuta Suzuki, Hiroyoshi Yamada, Ryoichi Sato (Niigata Univ.) AP2022-37 SANE2022-22 SAT2022-18
Recently, classification of ground surfaces using Polarimetric Synthetic Aperture Radar (PolSAR) data has been expected ... [more] AP2022-37 SANE2022-22 SAT2022-18
pp.17-21(AP), pp.1-5(SANE), pp.7-11(SAT)
SANE 2021-11-11
14:30
Online Online Polarimetric analysis of ALOS-2/PALSAR-2 data for grasping state of damaged bridge
Koki Kuwabara, Ryoichi Sato, Yoshio Yamaguchi, Hiroyoshi Yamada (Niigata Univ.) SANE2021-47
In this report, we examine polarimetric scattering characteristics for grasping state of bridge under severe flood disas... [more] SANE2021-47
pp.79-82
EMT, IEE-EMT 2021-11-05
11:15
Online Online Quaternion convolutional neural networks for PolSAR land classification
Yuya Matsumoto, Ryo Natsuaki, Akira Hirose (UTokyo) EMT2021-43
We propose a quaternion convolutional neural network (QCNN) for Polarimetric synthetic aperture radar
(PolSAR) land cla... [more]
EMT2021-43
pp.76-81
SANE 2019-11-01
10:00
Overseas KOREA (Jeju) Experimental study on grasping seasonal change in paddy rice growth using quad-polarimetric SAR data
Takuya Hashimoto, Ryoichi Sato, Yoshio Yamaguchi, Hiroyoshi Yamada (Niigata Univ.) SANE2019-62
In this report, we examine polarimetric scattering characteristics for grasping seasonal change of paddy rice growth by ... [more] SANE2019-62
pp.71-75
SANE 2019-11-01
10:20
Overseas KOREA (Jeju) Study on Land Use Classification of PolSAR Data by Using Convolutional Neural Network
Nanako Saito, Masanori Gocho, Hiroyoshi Yamada, Ryoichi Sato, Yoshio Yamaguchi (Niigata Univ.) SANE2019-63
Polarimetric Synthetic Aperture Radar (PolSAR) has been attracting attention in ground target detection and classificati... [more] SANE2019-63
pp.77-82
AP 2019-08-22
11:55
Hokkaido Hokkai-Gakuen Univ. Fundamental Study on Land Use Classification of PolSAR Data by Using Machine Learning
Nanako Saito, Masanori Gocho, Hiroyoshi Yamada, Ryoichi Sato, Yoshio Yamaguchi (Niigata Univ.) AP2019-57
Polarimetric Synthetic Aperture Radar (PolSAR) has been attracting attention in ground target detection and classificati... [more] AP2019-57
pp.55-60
AP 2019-05-17
14:50
Hyogo Kanpo-no-yado Arima (Arima Onsen, Hyogo) STOKES-VECTOR-BASED DISCRIMINATOR FOR DISTINGUISHING CONIFEROUS AND BROAD-LEAVED FORESTS WITH L BAND POLSAR DATA
Taiga Saito, Fang Shang, Naoto Kishi (UEC) AP2019-14
(To be available after the conference date) [more] AP2019-14
pp.75-78
SANE 2018-11-08
14:30
Overseas China (Xuchang) Model-Based Target Classification Using Polarimetric Similarity with Coherency Matrix Elements
Maito Umemura, Yoshio Yamaguchi, Hiroyoshi Yamada (Niigata Univ.) SANE2018-59
In this report, we propose a model-based target classification technique using polarimetric similarity with the ensemble... [more] SANE2018-59
pp.21-26
SANE 2018-11-08
14:50
Overseas China (Xuchang) A Novel Method Using Convolutional Neural Network for Polarimetric SAR ship detection
Kan Jin, Junjun Yin, Jian Yang (Tsinghua Univ.) SANE2018-60
This paper presents a novel approach for ship detection in polarimetric synthetic aperture radar (POLSAR) image with the... [more] SANE2018-60
pp.27-30
MBE, NC
(Joint)
2018-03-14
10:00
Tokyo Kikai-Shinko-Kaikan Bldg. Hierarchical quaternion neural networks with self-organizing codebook for unsupervised PolSAR land classification
Hyunsoo Kim, Akira Hirose (Tokyo Univ.) NC2017-88
We propose a self-organizing codebook-based hierarchical polarization feature vector generation to realize an unsupervis... [more] NC2017-88
pp.121-126
EMT, IEE-EMT 2017-11-09
10:50
Yamagata Tendo Hotel (Tendo, Yamagata) Flexible Unsupervised PolSAR Land Classification System Based on Quaternion Neural Networks
Hyunsoo Kim, Akira Hirose (Tokyo Univ.) EMT2017-48
We propose a flexible unsupervised PolSAR land classification system based on quaternion neural networks. The existing ... [more] EMT2017-48
pp.37-42
SANE 2017-10-05
14:20
Tokyo Maison franco - japonaise (Tokyo) Unsupervised Adaptive PolSAR Land Classification System Using Quaternion Neural Networks
Hyunsoo Kim, Akira Hirose (Univ. of Tokyo) SANE2017-57
We propose an unsupervised adaptive PolSAR land classification system using quaternion neural networks. Most of the exis... [more] SANE2017-57
pp.73-78
SANE 2017-06-23
13:35
Kanagawa JAXA Sagamihara Campus Analysis of Flood Area in Colombia at the end of March 2017 using ALOS-2 Polarimetric Data
Shu Sengoku, Yoshio Yamaguchi, Hiroyoshi Yamada, Ryoichi Sato (Niigata Univ.) SANE2017-18
Flooding occurs around the world, and various damage has been reported. It is important to survey flooded area as soon a... [more] SANE2017-18
pp.31-36
SANE 2016-11-24
16:50
Overseas National Taipei University of Technology (NTUT) Experimental Study on Target Estimation for POLSAR by Using Millimeter Wave Automotive Radar
Jun Minotani, Hiroyoshi Yamada, Yoshio Yamaguchi (Niigata Univ.), Yuuichi Sugiyama (Fujitsu TEN) SANE2016-71
Sensing technology by automotive millimeter wave radar has been attracting attention for traffic accident prevention and... [more] SANE2016-71
pp.99-102
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