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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 9 of 9  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
Tokushima Naruto grand hotel
(Primary: On-site, Secondary: Online)
Arterial Blood Pressure Waveform Estimation from Photoplethysmogram under Inter-subject Paradigm by U-Net and Domain Adversarial Training
Rikuto Yoshizawa, Kohei Yamamoto, Tomoaki Ohtsuki (Keio) SeMI2022-96
Blood pressure (BP) estimation methods using photoplethysmogram (PPG) signals based on deep learning models have been ac... [more] SeMI2022-96
MI 2022-07-08
(Primary: On-site, Secondary: Online)
[Short Paper] Unsupervised Domain Adaptation for Liver Tumor Detection in Multi-Phase CT images Using Adversarial Learning with Maximum Square Loss
Rahul Kumar Jain (Ritsumeikan Univ.), Takahiro Sato, Taro Watasue, Tomohiro Nakagawa (tiwaki), Yutaro Iwamoto (Ritsumeikan Univ.), Xianhua Han (Yamaguchi Univ.), Lanfen Lin, Hongjie Hu (Zhejiang Univ.), Yen-Wei Chen (Ritsumeikan Univ.) MI2022-37
Liver tumor detection in multi-phase CT images is essential in computer-aided diagnosis. Deep learning has been widely ... [more] MI2022-37
PRMU, IPSJ-CVIM 2022-03-11
Online Online Hand Segmentation in Egocentric Videos by Combining UMA and MCD
Kenichi Suzuki, Katsufumi Inoue, Michifumi Yoshioka (Osaka Prefecture Univ.) PRMU2021-83
Domain shift in the egocentric video analysis is caused by the difference between shooting environment of training and t... [more] PRMU2021-83
PRMU 2021-12-16
Online Online Unsupervised Logo Detection Using Adversarial Learning from Synthetic to Real Images
Rahul Kumar Jain (Ritsumeikan Univ.), Takahiro Sato, Taro Watasue, Tomohiro Nakagawa (tiwaki), Yutaro Iwamoto (Ritsumeikan Univ.), Xiang Ruan (tiwaki), Yen-Wei Chen (Ritsumeikan Univ.) PRMU2021-31
Most of the existing deep learning based logo detection methods typically use a large amount of annotated training data,... [more] PRMU2021-31
CCS 2021-03-29
Online Online IMAS-GAN: Unsupervised Domain Translation without Cycle Consistency
Masashi Okada, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.) CCS2020-28
CycleGAN realizes the translation between domains without using pair data. However, the configuration of two GANs and th... [more] CCS2020-28
NLC 2020-09-10
Online Online Unsupervised Domain Adaptation for Dialogue Sequence Labeling -- Application to Contact Center Tasks --
Shota Orihashi, Naoki Makishima, Mana Ihori, Akihiko Takashima, Tomohiro Tanaka, Ryo Masumura (NTT) NLC2020-8
This paper presents an unsupervised domain adaptation for utterance-level sequence labeling of conversation in a contact... [more] NLC2020-8
MI 2020-01-30
Okinawa OKINAWAKEN SEINENKAIKAN Extracting and Visualization of Essential Features for Staining Translation of Pathological Images
Ryoichi Koga, Noriaki Hashimoto, Tatsuya Yokota (NIT), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (NUI), Ichiro Takeuchi, Hidekata Hontani (NIT) MI2019-116
In this manuscript, we propose a method for stain translation of pathology images. When one constructs a computer aided ... [more] MI2019-116
IBISML 2018-11-05
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation]
Kei Yonekawa, Hao Niu, Mori Kurokawa, Arei Kobayashi (KDDI Research) IBISML2018-103
(Advance abstract in Japanese is available) [more] IBISML2018-103
SP 2018-08-27
Kyoto Kyoto Univ. [Poster Presentation] An Experimental Study on Transforming the Emotion in Speech using GAN
Kenji Yasuda, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) SP2018-26
In domain transfer task deep learning has made it possible to generate more natural and highly accurate output. Especial... [more] SP2018-26
 Results 1 - 9 of 9  /   
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