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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 20  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IPSJ-CVIM 2024-05-15
13:45
Tokyo
(Primary: On-site, Secondary: Online)
Fine-tuning Large Language Models for Automatic Font Skeleton Generation: A First Attempt
Yuxuan Liu (Tokyo Tech), Yasuhisa Fujii (Google Research), Xinru Zhu, Kayoko Nohara (Tokyo Tech)
 [more]
PRMU, IPSJ-CVIM 2024-05-16
15:10
Tokyo
(Primary: On-site, Secondary: Online)
A Proposal for Generating Incorrect Pairs for the CLIP Learning based on Image Clustering
Rina Tagami, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto (Chukyo Univ.)
(To be available after the conference date) [more]
PRMU, IBISML, IPSJ-CVIM 2024-03-03
16:30
Hiroshima Hiroshima Univ. Higashi-Hiroshima campus
(Primary: On-site, Secondary: Online)
Assessment of the Utility of Tumor Location Information in MR Image Classification
Tsukasa Nishinakagawa, Yoshinari Takeishi, Jun'ichi Takeuchi (Kyushu Univ.) IBISML2023-43
MRI, or magnetic resonance imaging, is a medical imaging technique widely used in various healthcare settings. It utiliz... [more] IBISML2023-43
pp.21-28
NC, MBE, NLP, MICT
(Joint) [detail]
2024-01-24
14:00
Tokushima Naruto University of Education Exploration of Soft Palate Image Based Diagnostic System for High-Risk Individuals of Esophageal Cancer
Keishi Okubo, Masato Kiyama, Motoki Amagasaki, Kotaro Waki, Katsuya Nagaoka, Yasuhito Tanaka (Kumamoto Univ.) NC2023-41
Previous studies have shown that certain findings of the soft palate are associated with the risk of esophageal squamous... [more] NC2023-41
pp.17-22
CPSY, IPSJ-ARC, IPSJ-HPC 2023-12-06
10:55
Okinawa Okinawa Industry Support Center
(Primary: On-site, Secondary: Online)
CPSY2023-33 (To be available after the conference date) [more] CPSY2023-33
pp.36-41
WIT, SP, IPSJ-SLP [detail] 2023-10-14
16:40
Fukuoka Kyushu Institute of Technology
(Primary: On-site, Secondary: Online)
Sequence-to-sequence Voice Conversion for Electrolaryngeal Speech Enhancement with Multi-stage Pretraining and Fine-tuning Techniques
Ding Ma, Lester Phillip Violeta, Kazuhiro Kobayashi, Tomoki Toda (Nagoya Univ.) SP2023-32 WIT2023-23
Sequence-to-sequence (seq2seq) voice conversion (VC) models have great potential for electrolaryngeal (EL) speech to nor... [more] SP2023-32 WIT2023-23
pp.27-32
NLC, IPSJ-NL 2023-03-18
11:05
Okinawa OIST
(Primary: On-site, Secondary: Online)
Estimating Named Entity Label Representation for Generative Low-Resource NER
Yuya Sawada (NAIST), Hiroki Teranishi (RIKEN AIP), Hiroki Ouchi (NAIST), Yuji Matsumoto (RIKEN AIP), Taro Watanabe (NAIST) NLC2022-22
Named entity recognition (NER) system needs to identify the entities of novel entity types with fewer examples. Few-shot... [more] NLC2022-22
pp.16-21
PRMU 2022-10-21
15:25
Tokyo Miraikan - The National Museum of Emerging Science and Innovation
(Primary: On-site, Secondary: Online)
Features and Deep Learning Models Suitable for Speech Source Discrimination Method in Plural Voice User Interfaces Environment
Kengo Maeda, Takahiro Yoshida (TUS) PRMU2022-27
Under the situation that plural devices equipped with a voice user interface exist in the user’s environment in the near... [more] PRMU2022-27
pp.29-34
AP, MW
(Joint)
2022-09-15
15:05
Ehime The Museum of Art, EHIME
(Primary: On-site, Secondary: Online)
Radio Propagation Prediction using Fine-Tuning method with Few Data
Tatsuya Nagao, Takahiro Hayashi (KDDI Research) AP2022-82
Wireless communication systems, such as Beyond 5G, are expected to be essential social infrastructure, and numerous devi... [more] AP2022-82
pp.62-67
EA, SIP, SP, IPSJ-SLP [detail] 2022-03-01
14:20
Okinawa
(Primary: On-site, Secondary: Online)
Fast Distortion Pedal Modeling with Fine-Tuning
Haruki Shoji, Kento Yoshimoto, Daiki Saka, Hiroki Kuroda, Daichi Kitahara, Kenichiro Tanaka, Akira Hirabayashi (Ritsumeikan Univ.) EA2021-75 SIP2021-102 SP2021-60
We propose a fast modeling method for distortion pedals based on deep learning. For modeling many times with different p... [more] EA2021-75 SIP2021-102 SP2021-60
pp.70-75
EMM, EA, ASJ-H 2021-11-15
09:00
Online Online [Poster Presentation] A Study on Convergency of DNN Watermarking without Embedding Loss Function
Takuro Tanaka, Tatsuya Yasui, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) EA2021-35 EMM2021-62
Intellectual Property Rights protection related to Deep Neural Networks is an important issue due to the high cost of tr... [more] EA2021-35 EMM2021-62
pp.49-54
SP, IPSJ-SLP, IPSJ-MUS 2021-06-19
15:00
Online Online Investigation on fine-tuning with image classification networks for deep neural network-based musical instrument classification
Yuki Shiroma, Yuma Kinoshita, Sayaka Shiota, Hitoshi Kiya (TMU) SP2021-17
In this paper, we investigate abilities of channel conversion methods for fine-tuning with image classification networks... [more] SP2021-17
pp.75-79
MI 2021-03-16
13:30
Online Online Effect of Improving Versatility of Lung Nodules Classification Model by Fine-Tuning
Taku Ri, Tatsuya Yamazaki (Niigata Univ.) MI2020-72
In order to improve the survival rate of lung cancer patients, it is important to detect nodules at an early stage, but ... [more] MI2020-72
pp.102-107
PRMU, IPSJ-CVIM 2021-03-04
16:05
Online Online Media detection from cardiovascular OCT images based on deep learning
jiwei zhang, kai wang (wakayama univ), Takashi Kubo (Wakayama Medical Univ), haiyuan wu (wakayama univ) PRMU2020-80
Medical image segmentation is an important issue in determining whether medical images can provide reliable evidence in ... [more] PRMU2020-80
pp.65-70
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2021-02-18
13:25
Online Online A Note on Estimation of Semantic Content Based on a Question Answering Model Using Brain Activity Data while Viewing Images -- Improvement of Estimation Performance Based on Fine-tuning of the VQA model --
Saya Takada, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
In this paper, we propose a semantic content estimation method based on a question and answer generation model using bra... [more]
PRMU, CNR 2019-02-28
14:15
Tokushima   Local Zoo Guide Application using Image Recognition
Rabarison Misamanana Felicia, Kohei Kawanaka, Hiroki Tanioka, Tetsushi Ueta (Tokushima Univ.) PRMU2018-118 CNR2018-41
Most of the information for guide in the Tokushima zoo is in Japanese. However, it is difficult to understand Japanese g... [more] PRMU2018-118 CNR2018-41
pp.21-26
NLC, IPSJ-NL, SP, IPSJ-SLP
(Joint) [detail]
2018-12-12
11:00
Tokyo Waseda Univ. Nishiwaseda Campus Data augmentation using stereotypical reply for patients' tweet identification
Reine Asakawa, Tomoyosi Akiba (TUT) NLC2018-31
In this study, we try to identify patients' tweets for symptom surveillance using Twitter.
This functionality is indis... [more]
NLC2018-31
pp.55-60
PRMU, IBISML, IPSJ-CVIM [detail] 2018-09-21
10:00
Fukuoka   [Short Paper] Computer-Aided Diagnosis of Liver Cancers Using Deep Learning with Fine-tuning
Weibin Wang (Ritsumeikan Univ.), Dong Liang, Lanfen Lin, Hongjie Hu, Qiaowei Zhang, Qingqing Chen (Zhejiang Univ.), Yutaro lwamoto, Xianhua Han, Yen-Wei Chen (Ritsumeikan Univ.) PRMU2018-57 IBISML2018-34
Liver cancer is one of the leading causes of death world-wide. Computer-aided diagnosis plays an important role in liver... [more] PRMU2018-57 IBISML2018-34
pp.139-140
NLC, IPSJ-DC 2018-09-07
13:10
Tokyo Seikei University Short text categorization with fine-tuning
Kazuya Shimura, Jiyi Li, Fumiyo Fukumoto (Univ of Yamanashi) NLC2018-20
We propose an approach for multi-label categorization of short texts and explore the use of a hierarchical structure (HS... [more] NLC2018-20
pp.73-78
ITE-BCT, IE, CS, IPSJ-AVM 2008-12-11
13:25
Aichi Nagoya University An Iterative Approach for 3-D Model Generation Using Disparity Maps
Mehrdad Panahpour Tehrani, Akio Ishikawa, Shigeyuki Sakazawa, Atsushi Koike (KDDI R&D Labs) CS2008-40 IE2008-104
In this research, we address the problem of 3-D model generation from disparity maps. Given an inaccurate 3-D model, den... [more] CS2008-40 IE2008-104
pp.7-10
 Results 1 - 20 of 20  /   
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