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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 65  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2024-03-04
15:10
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
Zero-shot oral cytology classification: Exploring text and image features with BiomedCLIP
Kyungrok Hong, Keita Takeda (Nagasaki Univ.), Eiji Mitate (Kanazawa Medical Univ.), Tomoya Sakai (Nagasaki Univ.) MI2023-84
 [more] MI2023-84
pp.169-172
MBE, MICT, IEE-MBE [detail] 2023-01-17
09:50
Saga   Oral Cytology Based on Representation Learning of Visually Salient Cells
Kazuki Matsuo, Eiji Mitate, Tomoya Sakai (Nagasaki Univ.) MICT2022-44 MBE2022-44
We classify microscopically photographed cells for screening tests to find oral cancer in its early stages. Oral cancer ... [more] MICT2022-44 MBE2022-44
pp.7-12
MI 2022-09-15
14:00
Kanagawa
(Primary: On-site, Secondary: Online)
Unsupervised Cell Detection for Suppression of Background Information in Cytology
Keita Takeda, Kazuki Matsuo, Kohei Fujiwara, Eiji Mitate, Tomoya Sakai (Nagasaki Univ.) MI2022-57
(To be available after the conference date) [more] MI2022-57
pp.35-38
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-19
13:00
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
[Special Talk] Integrative technologies of mathematical modeling and deep Learning -- Three strategies to distill inductive biases --
Tomoya Sakai (Nagasaki Univ.) SIP2022-9 BioX2022-9 IE2022-9 MI2022-9
(To be available after the conference date) [more] SIP2022-9 BioX2022-9 IE2022-9 MI2022-9
pp.49-54
MI 2022-01-25
15:45
Online Online Exploiting Perfusion MR Features for Salivary Gland Tumor Classification
Keita Takeda, Misa Sumi, Tomoya Sakai (Nagasaki Univ.) MI2021-47
Learning perfusion features from dynamic contrast-enhanced MRI is effective for classification of salivary gland tumors.... [more] MI2021-47
pp.16-21
MI, MICT [detail] 2021-11-05
10:00
Online Online [Short Paper] Prediction of therapeutic response in Sjogren's syndrome using ultrasound images of parotid glands
Kohei Fujiwara, Takeda Keita, Yukinori Takagi, Miho Sasaki, Sato Eida, Ikuo Katayama, Misa Sumi, Tomoya Sakai (Nagasaki Univ.) MICT2021-30 MI2021-28
The purpose of this study was to predict the response to treatment of SS from ultrasound (US) images of salivary glands ... [more] MICT2021-30 MI2021-28
pp.15-16
MI 2021-07-08
14:00
Online Online Unsupervised deep learning with low-rank and sparse priors for blood vessel enhancement from free-breathing angiography
Ryoji Ishibashi, Tomoya Sakai (Nagasaki Univ.), Hideaki Haneishi (Chiba Univ.) MI2021-11
(To be available after the conference date) [more] MI2021-11
pp.11-14
PRMU 2020-12-17
17:15
Online Online Transfer learning from sparse models -- Two approaches and optimization issues --
Tomoya Sakai, Rabi Yamada, Ryoji Ishibashi, Hiroyuki Takada (Nagasaki Univ.) PRMU2020-52
 [more] PRMU2020-52
pp.80-85
PRMU, IPSJ-CVIM 2020-03-17
09:45
Kyoto
(Cancelled but technical report was issued)
Deep neural network representation and learning of low-rank and sparse approximation -- With application to celiac angiography under free breathing --
Ryohei Miyoshi, Tomoya Sakai (Nagasaki Univ.), Takashi Ohnishi, Hideaki Haneishi (Chiba Univ.) PRMU2019-91
Low-rank and sparse (L+S) approximation, a.k.a. stable and robust principal component analysis, is known to be suitable ... [more] PRMU2019-91
pp.133-138
EMCJ, MICT
(Joint)
2020-03-13
13:40
Tokyo Kikai-Shinko-Kaikan Bldg.
(Cancelled but technical report was issued)
Comparison of non-invasive measurement signals of neck surface deformation during repetitive saliva swallowing
Yukari Miyata, Tomoya Sakai, Amane Yoshiki, Misako Higashijima (Nagasaki Univ) MICT2019-56
Pneumonia risk due to silent aspiration increases with age as the swallowing ability declines. A new daily-usable device... [more] MICT2019-56
pp.23-27
MI 2019-01-22
09:35
Okinawa   Acceleration of angiographic region enhancement based on robust principal component analysis using parallel processing
Morio Kawabe, Yuri Kokura, Takashi Ohnishi, Hideyuki Kato, Yoshihiko Ooka (Chiba Univ.), Tomoya Sakai (Nagasaki Univ.), Hideaki Haneishi (Chiba Univ.) MI2018-59
Robust principal component analysis (RPCA) can extract vessel information from consecutive digital angiographic images. ... [more] MI2018-59
pp.1-4
MICT, MI 2018-11-06
14:50
Hyogo University of Hyogo Feature extraction of coarse/fine crackles and its improvement via sparse modeling techniques
Kosei Nishitsuji, Tomoya Sakai, Toshikazu Fukumitsu, Yasushi Obase (Nagasaki Univ.), Sueharu Miyahara (BIPS) MICT2018-48 MI2018-48
Medical experts have heuristically defined lung sound features and validated their relations with patients’ conditions i... [more] MICT2018-48 MI2018-48
pp.45-48
MICT, MI 2018-11-06
15:10
Hyogo University of Hyogo MICT2018-49 MI2018-49 (To be available after the conference date) [more] MICT2018-49 MI2018-49
pp.49-53
MICT, MI 2018-11-06
15:30
Hyogo University of Hyogo MICT2018-50 MI2018-50 (To be available after the conference date) [more] MICT2018-50 MI2018-50
pp.55-58
IBISML 2017-11-09
13:00
Tokyo Univ. of Tokyo Semi-Supervised AUC Optimization based on Positive-Unlabeled Learning
Tomoya Sakai, Gang Niu (UTokyo/RIKEN), Masashi Sugiyama (RIKEN/UTokyo) IBISML2017-40
Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced classif... [more] IBISML2017-40
pp.39-46
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-24
10:20
Okinawa Okinawa Institute of Science and Technology Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags
Han Bao (Univ. of Tokyo), Tomoya Sakai, Issei Sato (Univ. of Tokyo/RIKEN), Masashi Sugiyama (RIKEN/Univ. of Tokyo) IBISML2017-3
Multiple instance learning (MIL) is a variation of traditional supervised learning problems where data (referred to as b... [more] IBISML2017-3
pp.55-62
PRMU, IE, MI, SIP 2017-05-26
10:20
Aichi   Deep Subspace Methods -- Pattern Recognition using Hierarchical Structure of Linear Subspaces --
Hayato Itoh, Atsushi Imiya (Chiba Univ.), Tomoya Sakai (Ngasaki Univ.) SIP2017-18 IE2017-18 PRMU2017-18 MI2017-18
We introduce an new geodesic distance between images. This distance is defined as the Wasserstein distance between contr... [more] SIP2017-18 IE2017-18 PRMU2017-18 MI2017-18
pp.93-98
PRMU, CNR 2017-02-19
11:20
Hokkaido   [Poster Presentation] Online Algorithm for Separating a Sequence of Optical Flow Fields with Low-rank and TV Regularization
Shun Ogawa, Tomoya Sakai (Nagasaki Univ.) PRMU2016-179 CNR2016-46
Estimation of camera egomotion and detection of moving object
both require separation of the apparent motions, a.k.a. t... [more]
PRMU2016-179 CNR2016-46
pp.155-156
PRMU, CNR 2017-02-19
11:20
Hokkaido   [Poster Presentation] Representation and Separation of Respiratory Sounds by Online Robust Principal Component Analysis
Kosei Nishitsuji, Shunpei Shiwa, Tomoya Sakai (Nagasaki Univ.) PRMU2016-180 CNR2016-47
This paper presents an online algorithm of separating lung sounds for computer-aided diagnosis. A lung sound consists of... [more] PRMU2016-180 CNR2016-47
pp.157-158
PRMU, CNR 2017-02-19
11:20
Hokkaido   [Poster Presentation] Compressed Sensing for 4D-MRI -- Fast Algorithm of Image Reconstruction --
Kohei Mochizuki, Tomoya Sakai (Nagasaki Univ.), Yukinojo Kitakami, Hideaki Haneishi (Chiba Univ.) PRMU2016-181 CNR2016-48
This work aims to reduce measurement time and improve the computational efficiency of four-dimensional magnetic resonanc... [more] PRMU2016-181 CNR2016-48
pp.159-160
 Results 1 - 20 of 65  /  [Next]  
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