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2020 – today
- 2023
[j20]Sai Yao, Daichi Kitahara, Hiroki Kuroda, Akira Hirabayashi:
Modal Interval Regression Based on Spline Quantile Regression. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 106(2): 106-123 (2023)- [j19]Laurent Condat
, Daichi Kitahara, Andrés Contreras, Akira Hirabayashi:
Proximal Splitting Algorithms for Convex Optimization: A Tour of Recent Advances, with New Twists. SIAM Rev. 65(2): 375-435 (2023) - 2022
- [j18]Hiroya Yamamoto, Daichi Kitahara, Hiroki Kuroda, Akira Hirabayashi:
Image Super-Resolution via Generative Adversarial Networks Using Metric Projections onto Consistent Sets for Low-Resolution Inputs. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 105-A(4): 704-718 (2022) - [j17]Daichi Kitahara, Hiroki Kuroda, Akira Hirabayashi, Eiichi Yoshikawa, Hiroshi Kikuchi, Tomoo Ushio:
Nonlinear Beamforming Based on Group-Sparsities of Periodograms for Phased Array Weather Radar. IEEE Trans. Geosci. Remote. Sens. 60: 1-19 (2022) - 2021
- [j16]Hiryu Kamoshita, Daichi Kitahara, Ken'ichi Fujimoto, Laurent Condat, Akira Hirabayashi:
Multiclass Dictionary-Based Statistical Iterative Reconstruction for Low-Dose CT. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 104-A(4): 702-713 (2021) - [c40]Daichi Kitahara, Rikako Kato, Hiroki Kuroda, Akira Hirabayashi:
Multi-Contrast CSMRI Using Common Edge Structures with LiGME Model. EUSIPCO 2021: 2119-2123 - [c39]Hiroki Kuroda, Daichi Kitahara, Akira Hirabayashi:
A Convex Penalty for Block-Sparse Signals with Unknown Structures. ICASSP 2021: 5430-5434 - 2020
- [c38]Kento Yoshimoto, Hiroki Kuroda, Daichi Kitahara, Akira Hirabayashi:
Deep Neural Network Modeling of Distortion Stomp Box Using Spectral Features. APSIPA 2020: 339-345 - [c37]Hiroya Yamamoto, Daichi Kitahara, Akira Hirabayashi:
Image Super-Resolution via Generative Adversarial Network Using an Orthogonal Projection. EUSIPCO 2020: 660-664 - [c36]Daichi Kitahara, Ke Leng, Yuji Tezuka, Akira Hirabayashi:
Simultaneous Spline Quantile Regression Under Shape Constraints. EUSIPCO 2020: 2423-2427 - [c35]Yuki Takahashi, Daichi Kitahara, Koichiro Matsuura, Akira Hirabayashi:
Determined Source Separation Using the Sparsity of Impulse Responses. ICASSP 2020: 686-690 - [c34]Ryusei Nakatsu, Daichi Kitahara, Akira Hirabayashi:
Non-Griffin-Lim Type Signal Recovery from Magnitude Spectrogram. ICASSP 2020: 791-795
2010 – 2019
- 2019
- [c33]Daichi Kitahara, Swathi Ananda, Akira Hirabayashi:
Optimization-Based Fundus Image Decomposition for Diagnosis Support of Diabetic Retinopathy. APSIPA 2019: 1565-1572 - [c32]Swathi Ananda, Daichi Kitahara, Akira Hirabayashi, K. R. Udaya Kumar Reddy:
Automatic Fundus Image Segmentation for Diabetic Retinopathy Diagnosis by Multiple Modified U-Nets and SegNets. APSIPA 2019: 1582-1588 - [c31]Laurent Condat, Daichi Kitahara, Akira Hirabayashi:
A Convex Lifting Approach to Image Phase Unwrapping. ICASSP 2019: 1852-1856 - [c30]Daichi Kitahara, Laurent Condat, Akira Hirabayashi:
One-dimensional Edge-preserving Spline Smoothing for Estimation of Piecewise Smooth Functions. ICASSP 2019: 5611-5615 - [c29]Hiryu Kamoshita, Taisuke Shibata, Daichi Kitahara, Ken'ichi Fujimoto, Akira Hirabayashi:
Low-Dose CT Reconstruction with Multiclass Orthogonal Dictionaries. ICIP 2019: 2055-2059 - 2018
- [c28]Daichi Kitahara, Maya Nakahara, Akira Hirabayashi, Eiichi Yoshikawa, Hiroshi Kikuchi, Tomoo Ushio:
Nonlinear Beamforming via Convex Optimization for Phased Array Weather Radar. APSIPA 2018: 1831-1835 - [i1]Hidetomo Kataoka, Takashi Ijiri, Kohei Matsumura, Jeremy White, Akira Hirabayashi:
Acoustic Probing for Estimating the Storage Time and Firmness of Tomatoes and Mandarin Oranges. CoRR abs/1809.10581 (2018) - 2017
- [j15]Naoki Nogami, Akira Hirabayashi, Takashi Ijiri, Jeremy White:
Toward Large-Pixel Number High-Speed Imaging Exploiting Time and Space Sparsity. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 100-A(6): 1279-1285 (2017) - [j14]Takashi Ijiri, Atsushi Nakamura, Akira Hirabayashi, Wataru Sakai, Takeshi Miyazaki, Ryutaro Himeno:
Automatic spin measurements for pitched Baseballs via consumer-grade high-speed cameras. Signal Image Video Process. 11(7): 1197-1204 (2017) - [c27]Ryosuke Kawami, Hidetomo Kataoka, Daichi Kitahara, Akira Hirabayashi, Takashi Ijiri, Shigeharu Shimamura, Hiroshi Kikuchi, Tomoo Ushio:
Fast high-quality three-dimensional reconstruction from compressive observation of phased array weather radar. APSIPA 2017: 44-49 - [c26]Chenmin Tang, Norihito Inamuro, Takashi Ijiri, Akira Hirabayashi:
Compressed sensing MRI using double sparsity with additional training images. ICASSP 2017: 801-805 - 2016
- [c25]Hidetomo Kataoka, Takashi Ijiri, Jeremy White, Akira Hirabayashi:
Acoustic probing to estimate freshness of tomato. APSIPA 2016: 1-5 - [c24]Ryosuke Kawami, Akira Hirabayashi, Nobuyuki Tanaka, Motoi Shibata, Takashi Ijiri, Shigeharu Shimamura, Hiroshi Kikuchi, Gwan Kim, Tomoo Ushio:
2-Dimensional high-quality reconstruction of compressive measurements of phased array weather radar. APSIPA 2016: 1-7 - [c23]Motoi Shibata, Norihito Inamuro, Takashi Ijiri, Akira Hirabayashi:
High accuracy reconstruction algorithm for CS-MRI using SDMM. APSIPA 2016: 1-6 - [c22]Akira Hirabayashi, Naoki Nogami, Takashi Ijiri, Laurent Condat:
Sequential image completion for high-speed large-pixel number sensing. EUSIPCO 2016: 948-952 - [c21]Takamichi Kojima, Takashi Ijiri, Jeremy White, Hidetomo Kataoka, Akira Hirabayashi:
CogKnife: Food recognition from their cutting sounds. ICME Workshops 2016: 1-6 - 2015
- [j13]Akira Hirabayashi, Norihito Inamuro, Aiko Nishiyama, Kazushi Mimura:
High-Quality Recovery of Non-Sparse Signals from Compressed Sensing - Beyond l1 Norm Minimization -. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 98-A(9): 1880-1887 (2015) - [c20]Norihito Inamuro, Akira Hirabayashi:
Improving the quality of compressed sensing MRI that exploits adjacent slice similarity. APSIPA 2015: 453-458 - [c19]Naoki Nogami, Akira Hirabayashi, Jeremy White, Laurent Condat:
Improvement of pixel enhancement algorithm for high-speed camera imaging using 3D sparsity. APSIPA 2015: 952-957 - [c18]Laurent Condat, Akira Hirabayashi:
Super-resolution of positive spikes by Toeplitz low-rank approximation. EUSIPCO 2015: 459-463 - [c17]Akira Hirabayashi, Nogami Nogami, Jeremy White, Laurent Condat:
Pixel enlargement in high-speed camera image acquisition based on 3D sparse representations. SiPS 2015: 1-6 - 2014
- [c16]Aiko Nishiyama, Yuki Yamanaka, Akira Hirabayashi, Kazushi Mimura:
Beyond ℓ1 norm minimization - High quality recovery of non-sparse compressible signals. APSIPA 2014: 1-4 - [c15]Takuya Umehara, Kazushi Mimura, Akira Hirabayashi:
A method for single frame super resolution with inpainting based on sparse dictionary learning. APSIPA 2014: 1-5 - 2013
- [j12]Akira Hirabayashi, Yosuke Hironaga, Laurent Condat:
Sampling Signals with Finite Rate of Innovation and Recovery by Maximum Likelihood Estimation. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 96-A(10): 1972-1979 (2013) - [j11]Akira Hirabayashi, Jumpei Sugimoto, Kazushi Mimura:
Complex Approximate Message Passing Algorithm for Two-Dimensional Compressed Sensing. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 96-A(12): 2391-2397 (2013) - [j10]Akira Hirabayashi, Kil Hyun Kwon, Jaekyu Lee:
Consistent Sampling with Multi-, Pre- and Post-Filterings. Int. J. Wavelets Multiresolution Inf. Process. 11(1) (2013) - [c14]Akira Hirabayashi, Jumpei Sugimoto, Kazushi Mimura:
Approximate message passing algorithm for complex separable compressed imaging. APSIPA 2013: 1-5 - [c13]Laurent Condat, Akira Hirabayashi, Yosuke Hironaga:
Recovery of nonuniformdirac pulses from noisy linear measurements. ICASSP 2013: 6014-6018 - [c12]Akira Hirabayashi, Yosuke Hironaga, Laurent Condat:
Sampling and recovery of continuous sparse signals by maximum likelihood estimation. ICASSP 2013: 6058-6062 - 2012
- [j9]Akira Hirabayashi:
Sampling and Reconstruction of Periodic Piecewise Polynomials Using Sinc Kernel. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 95-A(1): 322-329 (2012) - [j8]Akira Hirabayashi:
Consistent Sampling and Signal Reconstruction in Noisy Under-Determined Case. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 95-A(3): 631-638 (2012) - [c11]Akira Hirabayashi, Takuya Iwami, Shuji Maeda, Yosuke Hironaga:
Reconstruction of the sequence of Diracs from noisy samples via maximum likelihood estimation. ICASSP 2012: 3805-3808 - [c10]Akira Hirabayashi, Pier Luigi Dragotti:
Line-edge extraction based on E-spline acquisition model and a fast optimization algorithm. ICIP 2012: 89-92 - 2010
- [j7]Akira Hirabayashi:
Fast Surface Profiling by White-Light Interferometry Using Symmetric Spectral Optical Filter. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 93-A(2): 542-549 (2010) - [c9]Akira Hirabayashi, Pier Luigi Dragotti:
E-spline sampling for precise and robust line-edge extraction. ICIP 2010: 909-912
2000 – 2009
- 2009
- [j6]Akira Hirabayashi:
Consistent Sampling and Efficient Signal Reconstruction. IEEE Signal Process. Lett. 16(12): 1023-1026 (2009) - [c8]Akira Hirabayashi:
Joint estimation of offset parameters and high-resolution images via l1-norm minimization principle. ICDSC 2009: 1-6 - 2008
- [c7]Akira Hirabayashi, Laurent Condat:
A study on interlaced sampling with unknown offsets. EUSIPCO 2008: 1-5 - 2007
- [j5]Akira Hirabayashi:
Image Magnification by a Compact Method with Preservation of Preferential Components. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 90-A(8): 1534-1541 (2007) - [j4]Akira Hirabayashi, Michael Unser:
Consistent Sampling and Signal Recovery. IEEE Trans. Signal Process. 55(8): 4104-4115 (2007) - [c6]Akira Hirabayashi, Laurent Condat:
Torwards a general formulation for over-sampling and under-sampling. EUSIPCO 2007: 1985-1989 - [c5]Akira Hirabayashi, Laurent Condat:
A Compact Image Magnification Method with Preservation of Preferential Components. ICIP (5) 2007: 385-388 - 2006
- [c4]Akira Hirabayashi, Takeshi Naito:
Signal Reconstruction by Projection Filter with Preservation of Preferential Components. KES (3) 2006: 1272-1279 - 2002
- [j3]Hidekazu Iwaki, Hidemitsu Ogawa, Akira Hirabayashi:
Optimally generalizing neural networks with the ability to recover from single stuck-at r faults. Syst. Comput. Jpn. 33(7): 114-123 (2002) - 2001
- [j2]Akiko Nakashima, Akira Hirabayashi, Hidemitsu Ogawa:
Error correcting memorization learning for noisy training examples. Neural Networks 14(1): 79-92 (2001) - [j1]Akira Hirabayashi, Hidemitsu Ogawa:
A family of projection learnings. Syst. Comput. Jpn. 32(5): 21-35 (2001)
1990 – 1999
- 1999
- [c3]Akira Hirabayashi, Hidemitsu Ogawa:
What can memorization learning do? IJCNN 1999: 659-662 - [c2]Akira Hirabayashi, Gintaras Ogawa:
A class of learning for optimal generalization. IJCNN 1999: 1815-1819 - 1996
- [c1]Akira Hirabayashi, Hidemitsu Ogawa:
Admissibility of memorization learning with respect to projection learning in the presence of noise. ICNN 1996: 335-340
Coauthor Index
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last updated on 2024-04-24 23:18 CEST by the dblp team
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