| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| ME, IEICE-EMM, IEICE-IE, IEICE-LOIS, IEE-CMN, IPSJ-AVM [detail] |
2023-09-07
09:50 |
Osaka |
Osaka Metropolitan Univ.
(Primary: On-site, Secondary: Online) |
Improving Performance of Convolutional Neural Network-Based Driver Behavior Recognition
Shengbiao Wang, Koji Iwano (Tokyo City Univ.) |
This study investigates the automatic recognition of driver behaviors using images captured by in-vehicle cameras for th... [more] |
ME2023-90
pp.7-12 |
| AIT, IIEEJ, AS, CG-ARTS |
2023-03-06
14:38 |
Tokyo |
Tokyo Polytechnic Univ. (Nakano)
(Primary: On-site, Secondary: Online) |
Mouse classification system used by players in the e-Sports scene.
Takuma Sugiura, Kazuya Ueki (Meisei Univ.) |
In recent years, e-Sports, in which computer games are regarded as sports competitions, has become increasingly popular.... [more] |
AIT2023-65
pp.111-114 |
| ME |
2022-07-22
16:20 |
Online |
Online |
Image Classification of Cancer Cells Treated with IRDAptermer
Rahman Rawnak Mim, Yuuka Yamagata, Yoshiro Chuman, Shogo Muramatsu (Niigata Univ.) |
This work evaluates convolutional neural network (CNN)-based image classifiers for determining the effect of a cell memb... [more] |
ME2022-70
pp.23-26 |
| IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-20
16:20 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
Visualization of Important Features for Classifier Decisions using Deep Image Synthesis
Yushi Haku, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) |
It is difficult to know the basis for the decisions of machine learning models, and it is necessary to provide a highly ... [more] |
|
| AIT, IIEEJ, AS, CG-ARTS |
2022-03-08
09:53 |
Online |
Online |
Manga Inpainting with Author Classification and Line Drawing Clues
Hiroyuki Yokota (TUS), Ryosuke Furuta (UTokyo), Yukinobu Taniguchi (TUS), Ryota Hinami, Shonosuke Ishiwatari (Mantra) |
In order to translate Japanese manga into another language, it is necessary to recognize the contents and position of te... [more] |
AIT2022-51
pp.53-56 |
| 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
13:00 |
Online |
online |
Domain Incremental Leaning with Adaptive Loss Functions
Takumi Kawashima (UTokyo), Go Irie, Daiki Ikami (NTT), Kiyoharu Aizawa (UTokyo) |
During domain incremental learning of image classification task, the distribution of images continually change, and mode... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
10:15 |
Online |
online |
Classification of User's Device Possession Position and Behavior by Using Deep Metric Learning
Rui Kitahara, Lifeng Zhang (Kyutech) |
With the widespread use of smartphones, there have been efforts to classify human behavior using built-in sensors. Howev... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
11:10 |
Online |
online |
Enhancing Personalized Food Image Classifier by Visual Attention and Class-Dependent Weighting
Seum Kim, Yoko Yamakata, Kiyoharu Aizawa (UTokyo) |
In a real-world setting, food records are very noisy and strongly imbalanced. Besides, inter-class similarity and intra-... [more] |
|
| 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 |
| BCT, IEICE-SIS |
2021-10-07
14:25 |
Online |
online |
Block-wise Transformation with Secret Key for Adversary Robust Defence of SVM model
Ryota Iijima, MaungMaung AprilPyone, Hitoshi Kiya (TMU) |
In this paper, we propose a method for implementing support vector machine (SVM) models that are robust against adversar... [more] |
|
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-18
11:35 |
Online |
Online |
A Note on Accurate Distress Image Classification of Road Structures Using Attention Map based on Text Data
Naoki Ogawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a correlation-aware attention branch network (CorABN) using multi-modal data for deterioration level... [more] |
MMS2021-4 ME2021-4 AIT2021-4
pp.17-21 |
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-18
15:40 |
Online |
Online |
Texture Analysis and Evaluation of the Shitsukan Research Database Based on Luminance Information
Norifumi Kawabata (Tokyo Univ. of Science) |
One of texture component on objects and graphics is luminance. By strength of luminance, human visual perception for cla... [more] |
MMS2021-11 ME2021-11 AIT2021-11
pp.53-58 |
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-19
14:05 |
Online |
Online |
[Special Talk]
A Note on Discrimination of Road Surface Conditions Based on Deep Learning Using Road Images
Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we study the discrimination of road surface conditions based on deep learning using images captured by fi... [more] |
MMS2021-21 ME2021-21 AIT2021-21
pp.165-169 |
| SIP, ME |
2019-11-14
11:25 |
Kumamoto |
Sojo University, Main Campus |
Trial of three-dimensional extraction and classification of cell nucleus region in heart
Asuma Takematsu, Masahiro Migita, Masashi Toda, Yuichiro Arima (Kumamoto Univ.) |
In this study, after extracting the region of the cell nucleus from the cell nucleus image, I focused on only the typica... [more] |
ME2019-116
pp.9-12 |
| AIT, IIEEJ, AS, CG-ARTS |
2019-03-12
14:00 |
Tokyo |
Waseda Univ. |
LinDA:Features Extraction and Classification of Line Segments for Semi-Automatic Generation of Cartoon Background Images
Megumi Nomura, Masanori Nakayama, Issei Fujishiro (Keio Univ.) |
For cartoon novices, it is effective to reuse as their background images, line drawing materials drawn and opened to the... [more] |
AIT2019-139
pp.315-318 |
| ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] |
2019-02-20
11:00 |
Hokkaido |
Hokkaido Univ. |
A Note on Estimation of Rock Drilling Energy Using Tunnel Working Face Images
Kentaro Yamamoto, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In tunnel construction, it is important to grasp the geological condition of the rock to shorten the construction period... [more] |
MMS2019-32 HI2019-32 ME2019-54 AIT2019-32
pp.291-294 |
| ME |
2019-02-09
13:30 |
Kanagawa |
Kanto Gakuin University |
Video classification using signals and semantic level metadata for ambiguous video search
Ryunosuke Itabashi, Nobuyuki Yagi (Tokyo City Univ.) |
It is becoming possible to find the expected videos in the internet with considerable accuracy, but the developed techno... [more] |
ME2019-11
pp.31-34 |
| ME |
2018-02-24
14:30 |
Kanagawa |
Kanto Gakuin Univ. |
A consideration of video search for ambiguous aim
Ryunosuke Itabashi, Nobuyuki Yagi (Tokyo City Univ.) |
It is becoming possible to find the expected videos in the internet with considerable accuracy along with the progress o... [more] |
ME2018-61
pp.65-68 |
| IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] |
2018-02-15
13:45 |
Hokkaido |
Hokkaido Univ. |
A Note on Accuracy Improvement of Category Classification for Tourism Images in Image Sharing Services Using Deep Learning
Naoki Saito, Takahiro Ogawa (Hokkaido Univ.), Satoshi Asamizu (NIT, Kushiro College), Miki Haseyama (Hokkaido Univ.) |
This paper presents a category classification of tourism images in image sharing services. The proposed method obtains t... [more] |
MMS2018-14 HI2018-14 ME2018-14 AIT2018-14
pp.161-165 |