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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 253  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
RCC, ISEC, IT, WBS 2024-03-13
- 2024-03-14
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 2024-03-13
- 2024-03-14
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 of Tumors
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
EMM 2024-03-02
14:00
Overseas Day1:JEJU TECHNOPARK, Day2:JEJU Business Agency [Poster Presentation] Classification of AI generated images by sparse coding
Daishi Tanaka, Michiharu Niimi (KIT) EMM2023-89
In recent years, advancements in generative AI technologies have made it increasingly challenging for human vision to di... [more] EMM2023-89
pp.1-6
HCS 2024-03-02
09:35
Shizuoka Tokoha University(Shizuoka-Kusanagi Campus) Classification of Profile Images for SNS based on Demographical information, Identifiable information, Traceability and Linkability
Issei Kawamura, Sachiko Takagi (Tokiwa Univ.) HCS2023-89
(To be available after the conference date) [more] HCS2023-89
pp.7-12
ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] 2024-02-19
10:45
Hokkaido Hokkaido Univ. Brightness Adjustment based Countermeasure against Adversarial Examples
Takumi Tojo, Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) ITS2023-47 IE2023-36
Recently, image classification using deep learning AI has been used for in-vehicle AI, and its accuracy and response spe... [more] ITS2023-47 IE2023-36
pp.7-12
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
SIP, IT, RCS 2024-01-19
13:30
Miyagi
(Primary: On-site, Secondary: Online)
[Invited Talk] Problem of Adversarial Attacks on CNN-based Image Classifiers and Countermeasures
Minoru Kuribayashi (Tohoku Univ.) IT2023-67 SIP2023-100 RCS2023-242
It is well-known that discriminative models based on deep learning techniques may cause misclassification if adversarial... [more] IT2023-67 SIP2023-100 RCS2023-242
p.204
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
MI, MICT 2023-11-14
13:00
Fukuoka   Brain Disease Classification Based on Brain MRI Images Using 3D-CNN
Daisuke Hayashi, Akio Nagasaka, Yuji Mochizuki, Takayuki Hayashi (Hitachi), Takefumi Ueno (NHO Hizen Psychiatric Center) MICT2023-29 MI2023-22
Schizophrenia and Alzheimer’s disease are brain diseases that cause structural changes in the brain. In this paper, we c... [more] MICT2023-29 MI2023-22
pp.15-20
MI, MICT 2023-11-14
13:20
Fukuoka   Medical image diagnosis support system with image anonymization based on deep learning techniques
Katsuto Iwai, Ryuunosuke Kounosu (Toho Univ./AIST), Hirokazu Nosato (AIST), Yuu Nakajima (Toho Univ.) MICT2023-30 MI2023-23
When medical imaging AI models are hosted on cloud service there is a risk of sensitive medical images being leaked when... [more] MICT2023-30 MI2023-23
pp.21-24
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
MI 2023-09-08
11:20
Osaka
(Primary: On-site, Secondary: Online)
A Study on Identifying Gender Differences Using Deep Learning from Retinal Fundus Images
Shota Tsutsui (Waseda Univ.), Ichiro Maruko, Moeko Kawai (TWMU), Yoichi Kato, Jun Ohya (Waseda Univ.) MI2023-17
Previous studies show that a properly designed and trained deep learning algorithm is capable to identify the gender of ... [more] MI2023-17
pp.8-11
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
 Results 1 - 20 of 253  /  [Next]  
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