Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
RCC, RCS, SeMI, NS, SR, RISING (Joint) |
2024-07-19 10:25 |
Hokkaido |
Hokkaido Citizens Activities Promotion Center (Primary: On-site, Secondary: Online) |
Fundamental study on acoustic signal noise reduction using UNet and UNet3+ Sora Matsuo, Mari Ueda, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2024-33 |
A method has been proposed to remove noise using a deep learning model by converting noise-added source data into images... [more] |
SeMI2024-33 pp.85-90 |
ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2024-02-20 12:45 |
Hokkaido |
Hokkaido Univ. |
3D CG Coded Image Noise Removal and Quality Assessment Based on Optimal Design of Total Variation Regularization Norifumi Kawabata (Kanazawa Gakuin Univ.) ITS2023-67 IE2023-56 |
Sparse coding techniques, which reproduce and represent images with as few combinations as possible from a small amount ... [more] |
ITS2023-67 IE2023-56 pp.112-117 |
IE, CS, IPSJ-AVM [detail] |
2023-12-11 16:25 |
Fukuoka |
Kyushu Institute of Technology (Primary: On-site, Secondary: Online) |
[Special Invited Talk]
Considerations on Image Processing, Coding and Sensing Seishi Takamura (Hosei Univ.) CS2023-84 IE2023-26 |
In image/video coding, the input signal may be coded as-is, but image processing, such as noise removal, for example, ma... [more] |
CS2023-84 IE2023-26 p.17 |
NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-13 14:50 |
Ishikawa |
The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
Investigation of noise removal using U-Net and voice recognition performance improvement
-- for train running noise -- Jian Lin, Shota Sano, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2022-26 |
A method for converting noisy sound into images to remove the noise has been proposed. We are attempting to remove train... [more] |
SeMI2022-26 pp.34-39 |
EA |
2022-05-13 16:25 |
Online |
Online |
Study on noise reduction with a single noisy speech based on Double-DIP Hien Oonaka (NITTC), Takuya Fujimura (Nagoya Univ.), Ryoichi Miyazaki (NITTC) EA2022-12 |
This paper proposes a new noise reduction method with an untrained Deep Neural Network ( DNN) for a single noisy speech.... [more] |
EA2022-12 pp.54-61 |
MBE, NC (Joint) |
2022-03-03 15:30 |
Online |
Online |
EEG style transfer for sleep stage scoring using deep learning Naoki Omiya (Univ. of Tsukuba), Kazumasa Horie (CCS), Hiroyuki Kitagawa (IIIS) NC2021-66 |
Sleep stage scoring is a clinical inspection to identify in which sleep stages the patients are from their biological si... [more] |
NC2021-66 pp.106-111 |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-21 12:45 |
Online |
Online |
Quality Assessment for 3D CG Image Colorization Using Visible Digital Watermarking after Noise Removal Based on Sparse Dictionary Learning Coding Norifumi Kawabata (Hokkaido Univ.) |
Thus far, we discussed to represent image data whether it is possible or not to represent meaning image how requirement ... [more] |
|
EA, US (Joint) |
2021-12-22 13:30 |
Kumamoto |
Sojo University |
[Poster Presentation]
A Study on Estimating TDoA of Sound in Reverberant Environment Yudai Suzuki (UTokyo), Tsutomu Ikegami (AIST), Tomohiro Kudoh (UTokyo) EA2021-58 |
The measurement of the time difference of arrival (TDoA) of sound is improved by coupling reverberation removal filters... [more] |
EA2021-58 pp.7-12 |
SRW, SeMI, CNR (Joint) |
2021-11-26 15:00 |
Tokyo |
Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
A Study on Removal of Train Running Noise using U-Net for Spectrogram Images Motoki Ichikawa, Shota Sano, Jian Lin, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SRW2021-49 SeMI2021-48 CNR2021-23 |
In this manuscript, we present the results of a study on the effect of speech denoising using spectrogram images obtaine... [more] |
SRW2021-49 SeMI2021-48 CNR2021-23 pp.74-78(SRW), pp.61-65(SeMI), pp.51-55(CNR) |
SeMI, IPSJ-MBL, IPSJ-DPS, IPSJ-ITS |
2021-05-27 09:50 |
Online |
Online |
Investigation and Evaluation Experiment of Noise Removal for Voice Recognition in Specific Noisy Environment Shota Sano, Fumitaka Murakami, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2021-2 |
In this manuscript, the noise removal performance and speech recognition accuracy is described when noise is removed by ... [more] |
SeMI2021-2 pp.5-10 |
EMM, IT |
2021-05-21 13:10 |
Online |
Online |
A Study of Detecting Adversarial Examples Using Sensitivities to Multiple Auto Encoders Yuma Yamasaki, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.), Huy Hong Nguyen, Isao Echizen (NII) IT2021-11 EMM2021-11 |
By removing the small perturbations involved in adversarial examples, the image classification result returns to the cor... [more] |
IT2021-11 EMM2021-11 pp.60-65 |
EMM |
2021-03-04 14:15 |
Online |
Online |
[Poster Presentation]
Detection of Adversarial Examples in CNN Image Classifiers Using Features Extracted with Multiple Strengths of Filter Akinori Higashi, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.), Huy Hong Nguyen, Isao Echizen (NII) EMM2020-70 |
Deep learning has been used as a new method for machine learning, and its performance has been significantly improved. A... [more] |
EMM2020-70 pp.19-24 |
EA, US, SP, SIP, IPSJ-SLP [detail] |
2021-03-03 10:25 |
Online |
Online |
Remote Sensing Data Restoration by Constraining the Gradients of Stripe Noise Kazuki Naganuma, Saori Takeyama, Shunsuke Ono (Titech) EA2020-60 SIP2020-91 SP2020-25 |
This paper proposes an effective and efficient restoration methods for remote-sensing data by constraining the gradient ... [more] |
EA2020-60 SIP2020-91 SP2020-25 pp.5-8 |
EA |
2020-12-14 10:05 |
Online |
Online |
Speech Signal Detection Based on Bayesian Estimation by Observing Air-Conducted Speech under Existence of Surrounding Noise with Aid of Bone-Conducted Speech Akira Ikuta, Hisako Orimoto (Prefectural Univ. of Hiroshima), Kouji Hasegawa (Hiroshima Prefectural Technology Research Inst.) EA2020-48 |
When applying speech recognition systems to actual circumstances such as inspection and maintenance operations in indust... [more] |
EA2020-48 pp.13-18 |
SIS |
2020-12-01 15:15 |
Online |
Online |
A Proposal of Convolutional Neural Networks detecting and removing noise for Random-Valued Impulse Noise Denoising Yukiya Fukuda (Kytutech), Ryosuke Kubota (NITUC), Hakaru Tamukoh (Kyutech) SIS2020-34 |
When digital images are transmitted, Random-Valued Impulse Noise (RVIN) may cause image degradation. RVIN is known as no... [more] |
SIS2020-34 pp.35-40 |
SeMI |
2020-01-31 13:00 |
Kagawa |
|
Basic Evaluation of Environmental Noise Removal for Improving Alarm Sound Source Classification Performance Takeru Kadokura, Yuuki Hashizume, Yuusuke Kawakita, Hiroshi Tanaka (Kanagawa Institute of Technology) SeMI2019-114 |
The authors are studying a method to classify ringing devices with high accuracy using neural networks from indoor alarm... [more] |
SeMI2019-114 pp.57-62 |
EA |
2019-12-12 14:00 |
Fukuoka |
Kyushu Inst. Tech. |
Removal of musical noise using deep learning without pre-training Takuya Fujimura, Ryoichi Miyazaki (NITTC) EA2019-69 |
In this paper, we propose the musical noise elimination using the deep learning which does not require pre-training. It ... [more] |
EA2019-69 pp.23-29 |
IMQ |
2019-10-04 14:00 |
Osaka |
Osaka University |
3D CG Image Quality Assessment Including Noise Removal Based on Sparse Dictionary Learning Coding Norifumi Kawabata (Tokyo Univ. of Science) IMQ2019-6 |
By appearing of high-definition and high-quality images, it comes to increase many chance to process image big data. If ... [more] |
IMQ2019-6 pp.1-10 |
SIS |
2018-12-07 09:30 |
Yamaguchi |
Hagi Civic Center |
A Switching Noise Removal Filter Based on Convolutional Neural Networks and Its Application to Random-valued Impulse Noise Yukiya Fukuda, Ryosuke Kubota (NIT, UC) SIS2018-29 |
In order to remove random-valued impulse noise (RVIN) on a color image, we propose a novel switching denoising filter ba... [more] |
SIS2018-29 pp.41-46 |
SIS |
2018-12-07 09:50 |
Yamaguchi |
Hagi Civic Center |
A Proposal of Impulse Noise Removal Method Based on Boundary Discriminative Noise Detection Shan Xu (Nagoya City Univ.), Shi Bao (Inner Mongolia Univ. of Tech.), Go Tanaka (Nagoya City Univ.) SIS2018-30 |
A novel method for salt-and-pepper type impulse noise removal is proposed. In the proposed method, noise positions are d... [more] |
SIS2018-30 pp.47-50 |