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All Technical Committee Conferences (All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2021-03-15 15:15 |
Online | Online | Deep State-Space Modeling of FMRI Images with Disentangle Attributes Koki Kusano (Kobe Univ.), Takashi Matsubara (Osaka Univ.), Kuniaki Uehara (Osaka Gakuin Univ.)  MI2020-59 |
(To be available after the conference date) [more] | MI2020-59 pp.56-61 |
| MI | 2021-03-16 13:15 |
Online | Online | [Short Paper]
Feature extraction using AutoEncorder from nodular shadows on chest CT images Yuta Tanaka, Takeshi Hara, Xiangrong Zhou (Gifu Univ.), Masaki Matsusako, Taiki Nozaki (St. Luke's Hosp.) MI2020-71 |
(To be available after the conference date) [more] | MI2020-71 pp.99-101 |
| EMM | 2021-03-04 14:15 |
Online | Online | [Poster Presentation]
Detection of Adversarial Examples in CNN Image Classifiers Using Features Extracted with Multiple Strengths of Filter Akinori Higashi, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.), Huy Hong Nguyen, Isao Echizen (NII) EMM2020-70 |
Deep learning has been used as a new method for machine learning, and its performance has been significantly improved. A... [more] | EMM2020-70 pp.19-24 |
| EMM | 2021-03-05 10:20 |
Online | Online | Analysis of visual subjective evaluation for qualities of food taste using machine learning techniques Yoshiyuki Sato (Tohoku Univ.), Kazuya Matsubara, Yuji Wada (Ritsmeikan Univ.), Nobuyuki Sakai, Satoshi Shioiri (Tohoku Univ.) EMM2020-77 |
In this study, we conducted an experiment to collect human subjective judgments about taste (e.g. sweetness, spiciness) ... [more] | EMM2020-77 pp.58-62 |
| PRMU, IPSJ-CVIM | 2021-03-04 10:30 |
Online | Online | Learning Convolutional Neural Networks with Spatial Frequency Loss Naoyuki Ichimura (AIST) PRMU2020-73 |
The pixel-wise L2 and pixel-wise L1 losses have been commonly used to measure the consistency between images in learning... [more] | PRMU2020-73 pp.25-30 |
| PRMU, IPSJ-CVIM | 2021-03-04 16:20 |
Online | Online | VQA for Medical Image Data based on Image Feature Extraction and Fusion Hideo Umada, Masaki Aono (TUT) PRMU2020-81 |
In recent years, there has been a remarkable growth in research on deep learning in the fields of computer vision and na... [more] | PRMU2020-81 pp.71-76 |
| PRMU, IPSJ-CVIM | 2021-03-05 14:40 |
Online | Online | Retrieving Interesting Planetary Images based on Captions Hiya Roy, Toshihiko Yamasaki, Tatsuaki Hashimoto (UTokyo) PRMU2020-95 |
Planetary images are collected by sophisticated imaging devices onboard the orbiting or roving spacecraft. As the number... [more] | PRMU2020-95 pp.151-156 |
| IN, NS (Joint) |
2021-03-04 09:50 |
Online | Online | Person Tracking Method Based on Edge-to-Edge Cooperation for Specific Person Search Ryota Kawase, Masaki Murakami, Yoshihiko Uematsu, Satoru Okamoto, Naoaki Yamanaka (Keio Univ.) NS2020-125 |
The face recognition application is playing an active role in various cases such as unattended reception of visitors. Th... [more] | NS2020-125 pp.13-18 |
| BioX, CNR | 2021-03-02 15:30 |
Online | Online | Visual place recognition from eye reflection Yuki Ohshima, Kyosuke Maeda, Yusuke Edamoto, Atsushi Nakazawa (Kyoto Univ.) BioX2020-48 CNR2020-21 |
The cornea in the human eye reflects incoming environmental light, which means we can obtain information about the surro... [more] | BioX2020-48 CNR2020-21 pp.44-49 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-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] | |
| IE, ITS, ITE-MMS, ITE-ME, ITE-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] | |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2021-02-18 16:40 |
Online | Online | A note on improvement of image sentiment analysis based on introduction of image captioning Yun Liang, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Recently, with the popularization of social network services, the images uploaded by users have been increasing. Users t... [more] | |
| NC, NLP (Joint) |
2021-01-22 09:40 |
Online | Online | On decoding left-right movement intention of single arm from EEG Mitsuhiko Inaba, Kazushi Ikeda (NAIST), Motoaki Kawanabe (ATR) NC2020-35 |
Brain-machine interface (BMI) is a technology that supports people by manipulating external devices using only changes i... [more] | NC2020-35 pp.18-23 |
| ICM, LOIS | 2021-01-21 18:10 |
Online | Online | Two-Layered QR Codes and Their Principles
-- Development of Hologram QR Codes -- Hiroya Kawahara, Kohei Yamasaki (Kobe Univ.), Makoto Takita (University of Hyogo), Yoshiaki Shiraishi, Masakatu Morii (Kobe Univ.) ICM2020-48 LOIS2020-36 |
The Quick Response (QR) code is used for various purposes, such as accessing web pages, payment, etc. The QR codes which... [more] | ICM2020-48 LOIS2020-36 pp.81-86 |
| PRMU | 2020-12-18 15:10 |
Online | Online | A Hybrid Sampling Strategy for Improving the Accuracy of Image Classification with less Data Ruiyun Zhu, Fumihiko Ino (Osaka Univ.) PRMU2020-62 |
This paper proposes a hybrid sampling strategy to improve learning accuracy with less training data for image classifica... [more] | PRMU2020-62 pp.139-144 |
| PRMU | 2020-12-18 15:25 |
Online | Online | Multi-Task Attention Learning for Fine-grained Recognition Dichao Liu (NU), Yu Wang (Rits), Kenji Mase (NU), Jien Kato (Rits) PRMU2020-63 |
Due to its inter-class similarity and intra-class variation, Fine-Grained Image Classification (FGIC) is an intrinsicall... [more] | PRMU2020-63 pp.145-150 |
| PRMU | 2020-12-18 16:20 |
Online | Online | [Short Paper]
Case Discrimination: Self-supervised Learning for classification of Medical Image Haohua Dong, Yutaro Iwamoto (Ritsumeikan Univ.), Xianhua Han (Yamaguchi Univ.), Lanfen Lin (Zhejiang Univ.), Hongjie Hu, Xiujun Cai (Sir Run Run Shaw Hospital), Yen-Wei Chen (Ritsumeikan Univ.) PRMU2020-64 |
Deep Learning provides exciting solutions to problems in medical image analysis and is regarded as a key method for futu... [more] | PRMU2020-64 pp.151-155 |
| PRMU | 2020-12-18 17:15 |
Online | Online | Rethinking the local similarity in content-based image retrieval Longjiao Zhao (Nagoya Univ.), Yu Wang (Ritsumeikan Univ), Yoshiharu Ishikawa (Nagoya Univ.), Jien Kato (Ritsumeikan Univ) PRMU2020-68 |
Recently, Convolutional Neural Networks(CNN) have shown good performance in the image retrieval task. Especially, local ... [more] | PRMU2020-68 pp.172-176 |
| HCGSYMPO (2nd) |
2020-12-15 - 2020-12-17 |
Online | Online | Analysis of Relationship between Dishes and Foods towards Serving and Arrangement Support
-- Feature Analysis Focusing on Color Histogram -- Hayate Fukumoto, Mitsunori Matsushita, Ryosuke Yamanishi (Kansai Univ.) |
This paper investigate relationship between foods and plates based on each color histogram and its area. The goal of thi... [more] | |
| HCGSYMPO (2nd) |
2020-12-15 - 2020-12-17 |
Online | Online | Evaluation of lively face from spatial frequency characteristics of facial images Akihiro Tada, Nobu Mitani (POLA R&M) |
The morphological characteristics of the face and the condition of the skin reportedly affect evaluations of facial attr... [more] | |
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