Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 14:45 |
Hokkaido |
Hokkaido Univ. |
A Note on Improvement of Binauralization Performance Based on Multi-view Learning on 360° Videos Masaki Yoshida, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we propose a binaural audio generation method based on multi-view learning using 360◦ videos. Conventiona... [more] |
MMS2023-13 ME2023-33 AIT2023-13 pp.65-69 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 15:00 |
Hokkaido |
Hokkaido Univ. |
A Note on Specific Object Removal in Urban Scene Using Video Inpainting Approach Jiahuan Zhang, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido University) |
[more] |
MMS2023-14 ME2023-34 AIT2023-14 pp.71-74 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21 16:00 |
Hokkaido |
Hokkaido Univ. |
A note on gaze-dependent image re-ranking for content-based image retrieval Yuhu Feng, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
[more] |
MMS2023-18 ME2023-38 AIT2023-18 pp.89-93 |
MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-22 09:00 |
Hokkaido |
Hokkaido Univ. |
[Special Talk]
Efforts of Hokkaido university to develop data-driven interdisciplinary research Miki Haseyama, Yusuke Mizutani, Shingo Tanaka (Hokkaido Univ.) |
[more] |
MMS2023-19 ME2023-39 AIT2023-19 pp.179-180 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 13:00 |
Online |
online |
A note on multi-source model adaptation for semantic segmentation
-- Improving adaptation performance by learning model-invariant representation from multiple source models -- Zongyao Li, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
[more] |
MMS2022-7 ME2022-32 AIT2022-7 pp.37-41 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 13:15 |
Online |
online |
A Note on Improvement of Accuracy in Classification of Distress Images for Efficient Inspection of Road Structures
-- Introduction of Ratio of Similar Cases Based on Text Data -- Taisei Hirakawa, Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we propose a method for correcting the results of distress image classification using text data recorded ... [more] |
MMS2022-8 ME2022-33 AIT2022-8 pp.43-48 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 13:30 |
Online |
online |
A Note on Automatic Diagnosis of Helicobacter Pylori Infection Based on Self-Supervised Learning and Self-Knowledge Distillation Guang Li, Ren Togo (Hokkaido Univ.), Katsuhiro Mabe (Junpukai Health Maintenance Center), Shunpei Nishida (Olympus), Yoshihiro Tomoda (Olympus Medical Systems), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper proposes a novel method for automatic diagnosis of Helicobacter pylori (H. pylori) infection based on self-su... [more] |
MMS2022-9 ME2022-34 AIT2022-9 pp.49-52 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [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] |
MMS2022-17 ME2022-42 AIT2022-17 pp.87-90 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 16:45 |
Online |
online |
A Note on Disentanglement Using Deep Generative Model Based on Variational Autoencoder
-- Introduction of Regularization Losses Based on Metrics of Disentangled Representation -- Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we study disentangled representation learning using a deep generative model based on Variational Autoenco... [more] |
MMS2022-19 ME2022-44 AIT2022-19 pp.97-102 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 17:00 |
Online |
online |
A Note on Interest level Estimation Using Users' Behavior Information
-- Validating the Effectiveness of Feature Integration with Multiple Users -- Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we verify the effectiveness of feature integration with multi-user behavior information for interest leve... [more] |
MMS2022-20 ME2022-45 AIT2022-20 pp.103-107 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 17:15 |
Online |
online |
A Note on User Preference-Aware Music Playlist Generation Based on Reinforcement Learning and Knowledge Graph Keigo Sakurai, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
[more] |
MMS2022-21 ME2022-46 AIT2022-21 pp.109-112 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 13:55 |
Online |
online |
A Note on Multi-label Image Recognition in Anime Illustration Based on Graph Convolutional Networks Using Captioning Features Ziwen Lan, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
[more] |
MMS2022-22 ME2022-47 AIT2022-22 pp.161-165 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 14:10 |
Online |
online |
A Note on Transformer-based Scene Recognition in Soccer Videos Using Different Lengths of Clips Yaozong Gan, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
[more] |
MMS2022-23 ME2022-48 AIT2022-23 pp.167-170 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 14:25 |
Online |
online |
A Note on Visual Sentiment Prediction Based on Few-shot Learning using Knowledge Distillation Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
The prediction of visual sentiment can be useful to understand users' behaviors. Emotion theories underlying the sentime... [more] |
MMS2022-24 ME2022-49 AIT2022-24 pp.171-175 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 15:05 |
Online |
online |
A Note on Personalized Saliency Prediction Based on User Similarity Considering Object Information in Images Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a personalized saliency map (PSM) prediction method using a small amount of gaze data based on user ... [more] |
MMS2022-26 ME2022-51 AIT2022-26 pp.181-186 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21 15:20 |
Online |
online |
A Note on Electron Microscope Image Generation from Mix Proportion and Material Property via Generative Adversarial Network for Rubber Materials Rintaro Yanagi, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Estimating the properties of rubber materials from ingredients is necessary to accelerate rubber material development. A... [more] |
MMS2022-27 ME2022-52 AIT2022-27 pp.187-191 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22 15:20 |
Online |
online |
A Note on Perceived Visual Content Estimation Based on Compressed Reconstruction Network Using Brain Signals While Gazing on Images Takaaki Higashi, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido University) |
In this paper, we propose a method to reconstruct a perceived image using brain signals obtained during gazing images. S... [more] |
MMS2022-28 ME2022-53 AIT2022-28 pp.349-353 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22 16:05 |
Online |
online |
A note on improvement of distress classification using noise barrier images on highway via object detection method Yun Liang, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
[more] |
MMS2022-31 ME2022-56 AIT2022-31 pp.359-363 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22 16:30 |
Online |
online |
Relevance Analysis between Bio-signals of Engineers Inspecting Subway Tunnels and Their Inspection Behaviors Kaito Hirasawa, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents relevance analysis between bio-signals of engineers inspecting subway tunnels and their inspection b... [more] |
MMS2022-32 ME2022-57 AIT2022-32 pp.365-370 |
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22 16:45 |
Online |
online |
A Note on Accurate Distress Classification Using Deep Learning Considering Confidence in Attention map Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a note on accurate distress classification using deep learning considering confidence in attention m... [more] |
MMS2022-33 ME2022-58 AIT2022-33 pp.371-376 |