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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 14 of 14  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-15
14:30
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
Communication Size Reduction of Federated Learning based on Neural ODE Model
Yuto Hoshino, Hiroki Kawakami, Hiroki Matsutani (Keio Univ.) NS2022-59
(To be available after the conference date) [more] NS2022-59
pp.157-162
IMQ 2022-05-27
14:25
Tokyo   Classification-ESRGAN -- Synthesis of super-resolution images based on subject categorization --
Jingan Liu, Atsumu Harada, Naiwala P. Chandrasiri (Kogakuin Univ.) IMQ2022-3
In recent years, super-resolution techniques have been significantly developed based on deep learning. In particular, GA... [more] IMQ2022-3
pp.12-17
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] 2022-02-21
16:15
Online Online A Note on Realizing Adversarial Defense Based on Regularization of Multi-stage Squeeze-and-Excitation Features
Jiahuan Zhang, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Regularizing deep features is a common adversarial defense method. However, the existing methods do not further explore ... [more]
RCS, SIP, IT 2022-01-21
10:55
Online Online A lossless audio codec based on hierarchical residual prediction
Taiyo Mineo, Shouno Hayaru (UEC) IT2021-71 SIP2021-79 RCS2021-239
In this study, we propose a novel lossless audio codec that has precise predictive performance from the neural network a... [more] IT2021-71 SIP2021-79 RCS2021-239
pp.239-244
CS 2021-10-14
10:15
Online Online An Experimental Study on Improving Accuracy of Location Estimation in Finger Print Using CNN and ResNet
Yu Sakanishi, Satoru Aikawa, Shinichiro Yamamoto, Yuta Sakai (Univ of Hyogo) CS2021-52
Recently, indoor navigation system is one of the important technologies. We are studying
an indoor location estimation ... [more]
CS2021-52
pp.1-5
MI 2021-07-09
10:30
Online Online Applying Convolutional Network to Predict Pathology of Postchemotherapy Retroperitoneal Nodal Masses in Germ Cell tumors
Yoshimasa Iwano, Satoshi Nitta (Univ. of Tsukuba), Takahiro Kojima (Aichi Cancer Center), Hideki Kakeya (Univ. of Tsukuba) MI2021-15
The main treatment for advanced testicular cancer is chemotherapy and following surgical resection of residual masses. T... [more] MI2021-15
pp.25-30
MVE, IPSJ-CVIM 2021-01-22
15:35
Online Online [Short Paper] Basic examination about wiring status judgment of switchboard by image recognition
Keishi Nishimoto, Takeshi Hirama (itic.pref.ibaraki.jp) MVE2020-40
In the manufacturing industry, especially in the field of wiring work, the shortage of workers is an issue, and even beg... [more] MVE2020-40
pp.45-46
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-18
13:55
Okinawa Okinawa Institute of Science and Technology Additive or Concatenating Skip-connections Overcome the Degradation Problem of the Classic Feedforward Neural Network
Yasutaka Furusho, Kazushi Ikeda (NAIST) NC2019-17 IBISML2019-15
The classic feedforward neural networks like the multilayer perceptron (MLP) degrades its empirical risk by training eve... [more] NC2019-17 IBISML2019-15
pp.75-80(NC), pp.97-102(IBISML)
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-18
14:20
Okinawa Okinawa Institute of Science and Technology ResNet and Batch-normalization Improve Data Separation Ability
Yasutaka Furusho, Kazushi Ikeda (NAIST) NC2019-18 IBISML2019-16
The skip-connection and the batch-normalization (BN) in ResNet enable an extreme deep neural network to be trained with ... [more] NC2019-18 IBISML2019-16
pp.81-86(NC), pp.103-108(IBISML)
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] 2019-06-18
14:45
Okinawa Okinawa Institute of Science and Technology Theoretical Analysis of the Fixup Initialization for Fast Convergence and High Generalization Ability
Yasutaka Furusho, Kazushi Ikeda (NAIST) NC2019-19 IBISML2019-17
The Fixup initialization is a new initialization method of ResNet for a fast convergence with a high learning rate of SG... [more] NC2019-19 IBISML2019-17
pp.87-92(NC), pp.109-114(IBISML)
IBISML 2019-03-05
14:00
Tokyo RIKEN AIP Expressive power of skip connection and network architecture
Jumpei Nagase, Tetsuya Ishiwata (Shibaura Inst. of Tech.) IBISML2018-106
Model design is one of research topics in deep learning. Proposing a better model has been extensively studied, but ther... [more] IBISML2018-106
pp.9-15
IBISML 2019-03-06
10:00
Tokyo RIKEN AIP Effects of Batch-normalization on Fisher Information Matrix of ResNet
Yasutaka Furusho, Kazushi Ikeda (NAIST) IBISML2018-110
ResNet have intensively been studied and many techniques have been used for better performance.
Batch-normalization (BN... [more]
IBISML2018-110
pp.39-44
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
PRMU, CNR 2018-02-19
14:20
Wakayama   Verification of Shake Drop for neural network with deep residual block
Hiroki Morishita, Katsufumi Inoue, Michifumi Yoshioka (Osaka Prefecture Univ.) PRMU2017-157 CNR2017-35
(To be available after the conference date) [more] PRMU2017-157 CNR2017-35
pp.71-76
 Results 1 - 14 of 14  /   
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