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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 26  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
EA, SIP, SP, IPSJ-SLP [detail] 2022-03-01
14:20
Okinawa
(Primary: On-site, Secondary: Online)
Fast Distortion Pedal Modeling with Fine-Tuning
Haruki Shoji, Kento Yoshimoto, Daiki Saka, Hiroki Kuroda, Daichi Kitahara, Kenichiro Tanaka, Akira Hirabayashi (Ritsumeikan Univ.) EA2021-75 SIP2021-102 SP2021-60
We propose a fast modeling method for distortion pedals based on deep learning. For modeling many times with different p... [more] EA2021-75 SIP2021-102 SP2021-60
pp.70-75
SP, EA, SIP 2020-03-02
13:00
Okinawa Okinawa Industry Support Center
(Cancelled but technical report was issued)
[Poster Presentation] High-precision modeling of distortion stomp box by deep learning using spectral features
Kento Yoshimoto, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2019-124 SIP2019-126 SP2019-73
We propose a method for modeling distortion stomp box with high accuracy using a deep neural network, WaveNet. The conve... [more] EA2019-124 SIP2019-126 SP2019-73
pp.135-140
EA, SIP, SP 2019-03-14
13:30
Nagasaki i+Land nagasaki (Nagasaki-shi) [Poster Presentation] MR Image Reconstruction Using Two Types of Dictionaries and the Diagonalization of a BCCB Matrix
Kazuma Nakamoto, Kosuke Fujii, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2018-112 SIP2018-118 SP2018-74
We propose a high-quality MR image reconstruction method using both of an adaptive orthogonal dictionary and a pre-train... [more] EA2018-112 SIP2018-118 SP2018-74
pp.75-80
EA, SIP, SP 2019-03-14
13:30
Nagasaki i+Land nagasaki (Nagasaki-shi) [Poster Presentation] Image Super-Resolution via Generative Adversarial Network Considering Objective Quality
Hiroya Yamamoto, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2018-115 SIP2018-121 SP2018-77
We propose a super-resolution method based on a conventional technique using the generative adversarial network (GAN). T... [more] EA2018-115 SIP2018-121 SP2018-77
pp.93-98
PRMU, MI, IE, SIP 2018-05-18
14:45
Gifu   Low-Dose CT Image Reconstruction with Multiclass Dictionary Learning
Hiryu Kamoshita, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) SIP2018-15 IE2018-15 PRMU2018-15 MI2018-15
We propose a high-precision CT image reconstruction method from low-dose X-ray projection data. In conventional reconstr... [more] SIP2018-15 IE2018-15 PRMU2018-15 MI2018-15
pp.63-68
SIP, EA, SP, MI
(Joint) [detail]
2018-03-20
09:00
Okinawa   [Poster Presentation] Blind Source Separation Based on the Sparsity of Impulse Responses
Ryota Oda, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2017-164 SIP2017-173 SP2017-147
We propose a blind source separation (BSS) algorithm using a priori information of the mixing process based on the state... [more] EA2017-164 SIP2017-173 SP2017-147
pp.341-346
SIP, EA, SP, MI
(Joint) [detail]
2018-03-20
09:00
Okinawa   [Poster Presentation] Image Super-Resolution via Convolutional Neural Network Using An Orthogonal Projection Layer
Nobuyuki Baba, Hidetomo Kataoka, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2017-165 SIP2017-174 SP2017-148
We propose a super-resolution method using a convolutional neural network (CNN) that reduces obser- vation error during ... [more] EA2017-165 SIP2017-174 SP2017-148
pp.347-352
IT, SIP, RCS 2017-01-19
14:20
Osaka Osaka City Univ. High-Quality MR Imaging Based on Dictionary Learning Using Training Images and Observed Signals
Norihito Inamuro, Motoi Shibata, Tang Tammy, Takashi Ijiri, Akira Hirabayashi (Ritsumeikan Univ.) IT2016-67 SIP2016-105 RCS2016-257
 [more] IT2016-67 SIP2016-105 RCS2016-257
pp.123-128
RCS, AP
(Joint)
2016-11-24
14:45
Kyoto Kyoto International Community House [Invited Lecture] A study on compressive sensing data transfer for network operation of phased array weather radar
Hiroshi Kikuchi (Osaka Univ.), Ryosuke Kawami, Akira Hirabayashi, Takashi Ijiri (Ritsumeikan Univ.), Shigeharu Shimamura, Gwan Kim, Tomoo Ushio (Osaka Univ.) AP2016-113 RCS2016-197
 [more] AP2016-113 RCS2016-197
pp.35-40
PRMU, IE, MI, SIP 2016-05-19
15:10
Aichi   High accuracy reconstruction algorithm for CS-MRI using SDMM
Motoi Shibata, Norihito Inamuro, Takashi Ijiri, Akira Hirabayashi (Ritsumeikan Univ.) SIP2016-12 IE2016-12 PRMU2016-12 MI2016-12
We propose a high accuracy magnetic resonance imaging (MRI) reconstruction algorithm from compressively sampled measurem... [more] SIP2016-12 IE2016-12 PRMU2016-12 MI2016-12
pp.59-64
SIP 2015-08-20
09:55
Tokyo National Institute of informatics A study on pixel enhancement algorithm for high-speed camera imaging that exploits adjacent frame similarity
Naoki Nogami, Tomonori Kaneko, Akira Hirabayashi, Takashi Ijiri (Ritsumeikan Univ.) SIP2015-57
 [more] SIP2015-57
pp.35-40
PRMU, MI, IE, SIP 2015-05-15
09:30
Mie   Compressed sensing MRI using similarity of neighboring slices
Norihito Inamuro, Akira Hirabayashi (Ritsumeikan Univ.), Kazushi Mimura (Hiroshima City Univ.), Toshiyuki Kurihara, Toshiyuki Homma (Ritsumeikan Univ.) SIP2015-18 IE2015-18 PRMU2015-18 MI2015-18
 [more] SIP2015-18 IE2015-18 PRMU2015-18 MI2015-18
pp.93-98
CAS, SIP, MSS, VLD, SIS [detail] 2014-07-11
18:10
Hokkaido Hokkaido University High quality recovery of nonsparse signals from compressed sensing
Aiko Nishiyama, Yuki Yamanaka, Akira Hirabayashi (Ritsumeikan Univ.), Kazushi Mimura (Hiroshima City Univ.) CAS2014-24 VLD2014-33 SIP2014-45 MSS2014-24 SIS2014-24
We propose a novel algorithm for the recovery of non-sparse, but compressible signals from linear undersampled measureme... [more] CAS2014-24 VLD2014-33 SIP2014-45 MSS2014-24 SIS2014-24
pp.123-127
PRMU, MI, IE, SIP 2014-05-22
15:50
Aichi   Study on noise robustness of P300 detection for word sound stimuli
Shuichi Maeda (Yamaguchi Univ.), Akira Hirabayashi (Ritsumeikan Univ.), Toshihisa Tanaka (TUAT) SIP2014-10 IE2014-10 PRMU2014-10 MI2014-10
To achieve brain-computer interface (BCI) using sound stimuli in real environment, we evaluated the robustness of P300 d... [more] SIP2014-10 IE2014-10 PRMU2014-10 MI2014-10
pp.49-54
SIP, RCS 2013-02-01
10:50
Hiroshima Viewport-Kure-Hotel (Kure) Sampling and Recovery of Continuous Sparse Signals by Maximum Likelihood Estimation
Yosuke Hironaga, Akira Hirabayashi (Yamaguchi Univ.), Laurent Condat (Grenoble INP) SIP2012-102 RCS2012-259
We propose a maximum likelihood estimation approach for the recovery of continuously-defined sparse signals from noisy m... [more] SIP2012-102 RCS2012-259
pp.127-132
CAS, CS, SIP 2012-03-08
15:35
Niigata The University of Niigata Optimal Estimation of Step Line-Edge Based on E-spline Pixel Acqusition Model
Akira Hirabayashi, Naoya Kunisada (Yamaguchi Univ.), Pier Luigi Dragotti (Imperial College London) CAS2011-118 SIP2011-138 CS2011-110
We propose a line edge extraction algorithm based on an E-spline pixel acquisition model.
A straight line-edge can be d... [more]
CAS2011-118 SIP2011-138 CS2011-110
pp.65-70
MSS, CAS, VLD, SIP 2011-06-30
17:15
Okinawa Okinawa-Ken-Seinen-Kaikan A sampling theorem for periodic piecewise polynomials using sinc kernel
Akira Hirabayashi (Yamaguchi Univ.) CAS2011-16 VLD2011-23 SIP2011-45 MSS2011-16
We address a problem of sampling and reconstructing periodic piecewise polynomials
based on the theory for signals wit... [more]
CAS2011-16 VLD2011-23 SIP2011-45 MSS2011-16
pp.91-96
EA, SIP, SP 2011-05-13
11:15
Osaka Ritsumeikan Univ. An Extensoion of Consistent Sampling Theorem for Noisy Under-Determined Cases
Akira Hirabayashi (Yamaguchi Univ.) EA2011-24 SIP2011-24 SP2011-24
To discuss sampling theorem from the approximation point of view,
criterion for evaluation plays an important role.
Th... [more]
EA2011-24 SIP2011-24 SP2011-24
pp.137-142
CS, SIP, CAS 2011-03-03
14:10
Okinawa Ohhamanobumoto memorial hall (Ishigaki)( Robust Line-Edge Extraction Using Hyperbolic E-spline Sampling
Masahiko Takimoto, Akira Hirabayashi (Yamaguchi Univ.) CAS2010-135 SIP2010-151 CS2010-105
 [more] CAS2010-135 SIP2010-151 CS2010-105
pp.197-202
SP, EA, SIP 2010-05-27
13:25
Hyogo Konan Univ. (Hirao Seminar House) Precise Line-Edge Extraction from Low-Resolution Images by E-Spline Sampling
Akira Hirabayashi (Yamaguchi Univ.), Pier-Luigi Dragotti (Imperial Coll. London) EA2010-17 SIP2010-17 SP2010-17
The standard approach for line-edge extraction from image is Hough transform, which has many difficulties including limi... [more] EA2010-17 SIP2010-17 SP2010-17
pp.97-102
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