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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 203  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
ICSS, IPSJ-SPT 2024-03-21
16:10
Okinawa OIST
(Primary: On-site, Secondary: Online)
Considerations on Differential Privacy Mechanisms in MNIST
Naoki Kawahara, Pengxuan Wei, Ryunosuke Higashi, Kenta Okada, Tatsuhiro Yamatsuki, Atsuko Miyaji (Osaka Univ.) ICSS2023-79
In recent years, data utilization technologies, including machine learning, have been steadily advancing. One means of p... [more] ICSS2023-79
pp.71-78
RCC, ISEC, IT, WBS 2024-03-14
09:55
Osaka Osaka Univ. (Suita Campus) Comparison of accuracy of classification methods using machine learning for imaged malware
Kenta Usui, Hiroki Tanioka, Masahiko Sano, Kenji Matsuura, Tetsushi Ueta (Tokushima Univ.) IT2023-114 ISEC2023-113 WBS2023-102 RCC2023-96
In recent years, the damage caused by malware has become more serious, and the increase in the number of variants of exi... [more] IT2023-114 ISEC2023-113 WBS2023-102 RCC2023-96
pp.254-258
RCC, ISEC, IT, WBS 2024-03-14
10:20
Osaka Osaka Univ. (Suita Campus) Improving classification accuracy of imaged malware through data expansion
Kaoru Yokobori, Hiroki Tanioka, Masahiko Sano, Kenji Matsuura, Tetsushi Ueta (Tokushima Univ.) IT2023-115 ISEC2023-114 WBS2023-103 RCC2023-97
Although malware-based attacks have existed for years,
malware infections increased in 2019 and 2020.
One of the reaso... [more]
IT2023-115 ISEC2023-114 WBS2023-103 RCC2023-97
pp.259-264
IE, MVE, CQ, IMQ
(Joint) [detail]
2024-03-15
13:30
Okinawa Okinawa Sangyo Shien Center
(Primary: On-site, Secondary: Online)
Study on Leftovers Prediction from Food Images
Yuita Arum Sari, Atsushi Nakazawa (Okayama University) IMQ2023-86 IE2023-141 MVE2023-115
Leftover analysis is a valuable tool used by dietitians and nutritionists to assess a patient's calorie intake in health... [more] IMQ2023-86 IE2023-141 MVE2023-115
pp.390-395
MI 2024-03-03
09:41
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
A preliminary study on deep causal discovery model for image classification
Ryohei Motoda, Megumi Nakao (Kyoto Univ.) MI2023-33
Although saliency map used in image classification can visualize the regions correlated with predicted class, it cannot ... [more] MI2023-33
pp.11-14
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
MI 2024-03-03
16:42
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Using Label Uncertainty for Learning Cell Nuclei Type Classifier with Strongly Noisy Supervised Signals
Shingo Koide, Mauricio Kugler, Tatsuya Yokota (NIT), Koichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-57
In this study, we construct a type classifier for cell nuclei of malignant lymphomas. Labelling by type is not easy, eve... [more] MI2023-57
pp.79-80
CQ, CBE
(Joint)
2024-01-26
13:40
Kumamoto Kurokawa-Onsen
(Primary: On-site, Secondary: Online)
Image analysis technology for estimating the optimum tomato harvest timing and developed AI camera
Yasuhiro Okabe, Takefumi Hiraguri, Keita Endo, Naoki Yamada (NIT) CQ2023-66
If it were possible to mechanically estimate when tomatoes should be harvested timing, it would make harvesting easier f... [more] CQ2023-66
pp.76-81
NC, MBE, NLP, MICT
(Joint) [detail]
2024-01-25
09:00
Tokushima Naruto University of Education The Relationship Between Metrics in the Latent Variable Space and Image Classification Performance
Haruki Wakasa, Kenya Jin'no (Tokyo City Univ.) NLP2023-99 MICT2023-54 MBE2023-45
In recent years, models based on convolutional neural networks (CNNs) have exhibited high performance in image classific... [more] NLP2023-99 MICT2023-54 MBE2023-45
pp.78-81
NLP 2023-11-28
13:50
Okinawa Nago city commerce and industry association Considerations on the distribution of latent variables in CNNs
Mizuki Dai, Kenya Jin'no (Tokyo City Univ.) NLP2023-65
Abstract Fully comprehending the output decision mechanisms of neural networks is a critical challenge. This article foc... [more] NLP2023-65
pp.31-34
PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI 2023-11-16
16:50
Tottori
(Primary: On-site, Secondary: Online)
On Food Plant Classification from Luehdorfia Japonica Images using Multi-label Classification ABN
Tsubasa Hirakawa, Takaaki Arai, Takayoshi Yamashita, Hironobu Fujiyoshi, Yuichi Oba, Hiromichi Fukui (Chubu Univ.), Masaya Yago (Tokyo Univ.) PRMU2023-27
Butterfly is a familiar taxon. Because of the abundance of specimens and the ease of comparison between specimens, regio... [more] PRMU2023-27
pp.62-67
SR 2023-11-10
10:55
Miyagi
(Primary: On-site, Secondary: Online)
[Short Paper] On Model Transfer with Deep Joint Source Channel Coding
Katsuya Suto, Issa Matsumura, Junichiro Yamada (UEC) SR2023-58
Based on the source channel separation theorem, the current multimedia transfer system employs independently designed so... [more] SR2023-58
pp.61-63
MI 2023-09-08
10:05
Osaka
(Primary: On-site, Secondary: Online)
[Short Paper] Construction of Cell Nucleus Classifier using Complementary-Label Learning towards the Quantification of Grading for Follicular Lymphoma
Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-14
In this paper, we report the cell type classification from a pathological image toward the subtype classification of mal... [more] MI2023-14
pp.1-2
SIP 2023-08-07
12:50
Osaka Osaka Univ. (Suita) Convention Center
(Primary: On-site, Secondary: Online)
An Extension of Image Encryption for Vision Transformer Considering Privacy Protection
Haiwei Lin, Shoko Imaizumi (Chiba Univ.), Kiya Hitoshi (Tokyo Metropolitan Univ) SIP2023-46
In this paper, we propose an extended framework of access control for Vision Transformer (ViT).
The previous study acc... [more]
SIP2023-46
pp.1-6
SIP 2023-08-07
13:10
Osaka Osaka Univ. (Suita) Convention Center
(Primary: On-site, Secondary: Online)
A Perceptual Collation Method for Color Halftone Images Using Vision Transformer
Daiki Fujikawa, Shoko Imaizumi, Takahiko Horiuchi (Chiba Univ.) SIP2023-47
We propose an automatic collation method based on human perception in this paper.
The collation target of the propose... [more]
SIP2023-47
pp.7-12
AP, SANE, SAT
(Joint)
2023-07-12
09:50
Hokkaido The Citizen Activity Center
(Primary: On-site, Secondary: Online)
A Universal Method of Dataset Building for SAR Image Land-use Land-cover Classification and the Evaluation
Jing-Yuan Wang, Josaphat Tetuko Sri Sumantyo (Chiba Univ.) SANE2023-21
Because the awesome characteristics are shown by SAR, the images are widely used in remote sensing fields and various ap... [more] SANE2023-21
pp.1-6
MI 2023-05-18
16:00
Aichi Nagoya Congress Center Correlation Between Grid Masks in an Explanation Method for Image Classification
Kentaro Matsumoto, Yuji Ayatsuka (CRESCO) MI2023-5
One of the approaches to visualize the basis for image classification by machine learning is to use output values when c... [more] MI2023-5
pp.14-18
MI 2023-03-06
09:57
Okinawa OKINAWA SEINENKAIKAN
(Primary: On-site, Secondary: Online)
Multi-label multi-class estimation of pathology in high-resolution chest CT images using SRGAN
Tetsuya Asakawa, Riku Tsuneda, Yuki Sugimoto (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) MI2022-76
The purpose of this research, three pathologies (thickening, calcification, and cavitation) were accurately estimated as... [more] MI2022-76
pp.14-19
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-02
11:15
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
Dynamic Weight Scheduling for Long-tailed Visual Recognition
Xinyuan Li (Ritsumeikan Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Ritsumeikan Univ.) PRMU2022-78 IBISML2022-85
For long-tailed image recognition tasks, re-weighting is effective to alleviate data imbalance by assigning higher weigh... [more] PRMU2022-78 IBISML2022-85
pp.107-110
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-03
17:00
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
Continual learning combining Replay and Parameter Isolation Methods
Ryota Adachi, Toshikazu Wada (Wakayama Univ.) PRMU2022-121 IBISML2022-128
Deep Neural Networks (DNN) are used for various tasks such as image classification, but when a new task is trained on a ... [more] PRMU2022-121 IBISML2022-128
pp.335-340
 Results 1 - 20 of 203  /  [Next]  
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