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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 43  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE
(Joint)
2022-09-29
13:00
Miyagi Tohoku Univ.
(Primary: On-site, Secondary: Online)
Analysis of VGG Model through Interpretation in terms of Visual Cortex
Hikaru Higuchi (UEC), Toya Teramoto (Sony Group), Satoshi Suzuki (NTT), Hayaru Shouno (UEC)
 [more]
MBE, NC
(Joint)
2022-03-02
16:10
Online Online XMCD-CT Reconstruction Using Compressed Sensing
Tsukito Takizawa, Hayaru Shouno (The Univ. of Electro-Communications), Masaichiro Mizumaki (JASRI), Motohiro Suzuki (Kwansei Gakuin Univ.) NC2021-58
Observation of the magnetic domain structure is important for understanding the magnetic properties of materials includi... [more] NC2021-58
pp.62-67
NLP, MICT, MBE, NC
(Joint) [detail]
2022-01-23
11:45
Online Online Adversarial Training with Knowledge Distillation considering Intermediate Feature Representation in CNNs
Hikaru Higuchi (The Univ. of Electro-Communications), Satoshi Suzuki (former NTT), Hayaru Shouno (The Univ. of Electro-Communications) NC2021-44
Adversarial examples are one of the vulnerability attacks to the convolution neural network (CNN). The adversarialexampl... [more] NC2021-44
pp.59-64
NC, MBE
(Joint)
2021-03-03
13:25
Online Online Visualization of CNNs using Preferred Stimulus in Receptive Fields
Genta Kobayashi, Hayaru Shouno (UEC) NC2020-47
Convolutional neural networks have shown high performance at image processing task, and
they are interpreted by variou... [more]
NC2020-47
pp.25-30
NC, MBE
(Joint)
2021-03-03
13:50
Online Online Analysis of deep convolutional neural network texture representation using Portilla-Simoncelli statistics
Yusuke Hamano, Hayaru Shouno (UEC) NC2020-48
Recently, DCNN has achieved significant success in the field of computer vision. It is suggested that the DCNN, which ar... [more] NC2020-48
pp.31-36
SIP 2020-08-28
10:30
Online Online Improvement Convergence Rate of the Sign Algorithm by Natural Gradient Method
Taiyo Mineo, Hayaru Shouno (UEC) SIP2020-34
In lossless audio compression, it is essential to predictive residuals to be sparse, since we apply entropy codings to r... [more] SIP2020-34
pp.19-24
NLP, NC
(Joint)
2020-01-24
11:10
Okinawa Miyakojima Marine Terminal Proposal of Compression Method for Planetary Surface Image using Sparse Coding
Yoshifumi Uesaka, Hayaru Shouno (UEC) NC2019-65
In recent years, the demand for space development has been increasing. We treat an efficient image transmitting system f... [more] NC2019-65
pp.33-38
NLP, NC
(Joint)
2020-01-25
13:30
Okinawa Miyakojima Marine Terminal Estimation of the high-risk area of potential crime using sparse estimation and consideration of crime occurrence mechanism
Sho Ichigozaki (NPA/UEC), Takahiro Kawashima, Hayaru Shouno (UEC) NC2019-71
 [more] NC2019-71
pp.69-74
NC, MBE 2019-12-06
14:40
Aichi Toyohashi Tech Implementation of an FPGA-based energy-efficient MCMC method for 2D Lenz-Ising model
Patrick Tchicali, Hayaru Shouno (UEC) MBE2019-54 NC2019-45
MCMC methods are arguably one of the most useful sampling methods. MCMC while being very useful and practical remains a ... [more] MBE2019-54 NC2019-45
pp.55-60
MBE, NC 2019-10-11
15:00
Miyagi   Analysis of diffuse lung disease shadows using Bolasso feature selection method
Akihiro Endo (UEC), Kenji Nagata (NIMS), Shoji Kido (Osaka Univ.), Hayaru Shouno (UEC) MBE2019-33 NC2019-24
Diffuse lung disease is an intractable disease and abnormal shadows appear on lung X-ray CT images.
Since various patte... [more]
MBE2019-33 NC2019-24
pp.23-27
IT, ISEC, WBS 2019-03-07
16:55
Tokyo University of Electro-Communications [Invited Talk] Deepning and evolution of Deep learning technology
Hayaru Shouno (UEC) IT2018-88 ISEC2018-94 WBS2018-89
 [more] IT2018-88 ISEC2018-94 WBS2018-89
p.83
NC, MBE
(Joint)
2019-03-06
15:50
Tokyo University of Electro Communications PET Image Reconstruction by use of Dictionary Learning
Naohiro OKumura, Hayaru Shouno (UEC) NC2018-85
Nowadays, Positron Emission Tomography (PET) scan is focused in the field of pathological diagnosis.In order to obtain a... [more] NC2018-85
pp.221-226
NC, MBE
(Joint)
2019-03-06
16:15
Tokyo University of Electro Communications Examination of Super Resolution and Noise Removal for MicroCT Image
Miku Mashimo, Hayaru Shouno (UEC) NC2018-86
The purpose of this research is to increase the resolution of MicroCT (Computed Tomography) images.
The MicroCT image i... [more]
NC2018-86
pp.227-232
NC, MBE
(Joint)
2019-03-06
16:40
Tokyo University of Electro Communications Study on data augmentation using Fourier transform for texture image classification
Daigo Nitta, Hayaru Shouno (UEC) NC2018-87
In the field of medical imaging such like computed tomography analysis, it is difficult to prepare a sufficient amount o... [more] NC2018-87
pp.233-238
NLP, NC
(Joint)
2019-01-23
15:40
Hokkaido The Centennial Hall, Hokkaido Univ. Measuring the Convolution Neural Network similarities trained with different dataset using SVCCA
Toya Teramoto, Hayaru Shouno (UEC) NC2018-40
Deep Convolutional Neural Network (DCNN) is a successful model in the field of computer vision such like image classif... [more] NC2018-40
pp.11-16
MBE, NC
(Joint)
2018-03-13
11:15
Tokyo Kikai-Shinko-Kaikan Bldg. Application of U-Net to spine image extraction in CT image
Mikoto Kamata, Masayuki Kikuchi (Tokyo Univ.of Tech.), Hayaru Shouno (Univ. of Electro-Communications.), Isao Hayashi (Kansai Univ.), Kunihiko Fukushima (Fuzzy Logic Systems Inst.) NC2017-81
In this study, we aimed at automatic extraction of spinal parts in CT images using deep learning as a foothold for autom... [more] NC2017-81
pp.81-84
MBE, NC
(Joint)
2017-03-13
13:35
Tokyo Kikai-Shinko-Kaikan Bldg. A Generative Model of Textures Using Hierarchical Probabilistic Principal Component Analysis
Aiga Suzuki, Hayaru Shouno (UEC) NC2016-83
Modeling of natural textures in an important task for microscopic structure of natural images. Portilla and Simon-
cell... [more]
NC2016-83
pp.115-120
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
16:15
Toyama   The Validity of Network In Network as a Visual System -- From the Point of View of the Orientation Selectivity Map --
Satoshi Suzuki, Hayaru Shouno (UEC) PRMU2016-68 IBISML2016-23
In recent years, Deep Convolutional Neural Network (DCNN) has shown excellent performance in image recognition field. DC... [more] PRMU2016-68 IBISML2016-23
pp.113-120
SIP 2016-08-25
15:30
Chiba Chiba Institute of Technology, Tsudanuma Campus [Invited Talk] Applications of Deep learning for image diagnosis
Hayaru Shouno (UEC) SIP2016-76
The ``deep learning'' is the 3rd generation neural network technology, which is exhibiting its characteristics in the bi... [more] SIP2016-76
pp.23-24
MBE, NC
(Joint)
2016-03-23
10:50
Tokyo Tamagawa University A Study of Sparse Feature Learning in the Learning Process of Deep Convolutional Neural Network
Yoshihiro Kusano, Hayaru Shouno (UEC) NC2015-81
A study to make an image and a video high resolution with the improvement of the display and print technology is conduct... [more] NC2015-81
pp.65-70
 Results 1 - 20 of 43  /  [Next]  
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