[D-20] 情報論的学習理論と機械学習 | The Institute of Electronics, Information and Communication Engineers General Conference

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Session Details

一般セッションOpen Session : General Session

[D-20]情報論的学習理論と機械学習

Thu. Mar 7, 2024 9:00 AM - 12:00 PM JST
Thu. Mar 7, 2024 12:00 AM - 3:00 AM UTC

School of Integrated Arts and Sciences　K101(HIROSHIMA UNIVERSITY Higashi-Hiroshima campus)

Chair:Futami Futoshi

9:00 AM - 9:15 AM JST(12:00 AM - 12:15 AM UTC)Candidate for Academic Incentive Award

[D-20-01]Quantitative Evaluation by Deep Learning for Quality Control of himeric Mice with Humanized Livers

○Takumi Fujisawa¹, Tetsushi Koide¹, Masaki Takahashi², Mutsumi Inamatsu², Chise Tateno² (1. Research Institute for Nanodevices, Hiroshima University, 2. PhoenixBio Co., Ltd.)

9:15 AM - 9:30 AM JST(12:15 AM - 12:30 AM UTC)Career Explorer

[D-20-02]A Diagnosis Support System Capable of Lesion Segmentation and Local Classification for Colon Endoscopy

○Yongfei Wu¹, Daisuke Katayama¹, Tetsushi Koide¹, Toru Tamaki², Shigeto Yoshida³, Shin Morimoto⁴, Yuki Okamoto⁴, Shiro Oka⁴, Shinji Tanaka⁵ (1. Research Institute for Nanodevices, Hiroshima University, 2. Department of Computer Science, Nagoya Institute of Technology, 3. Department of Gastroenterology, Medical Corporation JR Hiroshima Hospital, 4. Department of Gastroenterology and Metabolism, Hiroshima University Hospital, 5. Department of Gastroenterology, JA Onomichi General Hospital)

9:30 AM - 9:45 AM JST(12:30 AM - 12:45 AM UTC)

[D-20-03]キクラゲのCG画像を用いたData Augmentationによる認識の一考察

○Ryuki Yamada¹, Ryo Matsumura², Hironori Kitakaze¹ (1. NIT, Oshima College, 2. SHUNAN Univ)

9:45 AM - 10:00 AM JST(12:45 AM - 1:00 AM UTC)

[D-20-04]Facial Image Synthesis Based on Textual Descriptions Using Contour Images

○Mizuki Moritaki¹, Hiroyuki Sato¹ (1. The University of Tokyo)

10:00 AM - 10:15 AM JST(1:00 AM - 1:15 AM UTC)

[D-20-05]Assesing Factuality in Vision Language Models

○Mariko Tomariguchi¹, Kohei Yamamoto¹, Hideaki Tamai¹ (1. OKI)

10:15 AM - 10:30 AM JST(1:15 AM - 1:30 AM UTC)

[D-20-06]An Empirical Study of Pretraining to Enhance Embedding Alignment in Vision-and-Language Models

○Satoshi Kawamura¹, Kohei Yamamoto¹, Mariko Tomariguchi¹, Hideaki Tamai¹ (1. OKI)

10:30 AM - 10:45 AM JST(1:30 AM - 1:45 AM UTC)

Break time

10:45 AM - 11:00 AM JST(1:45 AM - 2:00 AM UTC)

The Institute of Electronics, Information and Communication Engineers General Conference

Session Details

[D-20]情報論的学習理論と機械学習

[D-20-01]Quantitative Evaluation by Deep Learning for Quality Control of himeric Mice with Humanized Livers

[D-20-02]A Diagnosis Support System Capable of Lesion Segmentation and Local Classification for Colon Endoscopy

[D-20-03]キクラゲのCG画像を用いたData Augmentationによる認識の一考察

[D-20-04]Facial Image Synthesis Based on Textual Descriptions Using Contour Images

[D-20-05]Assesing Factuality in Vision Language Models

[D-20-06]An Empirical Study of Pretraining to Enhance Embedding Alignment in Vision-and-Language Models

Break time

[D-20-07]Algorithm for n-value+α classification model including unknown untrained data

[D-20-08]冗長な特徴が存在する場合の非線形回帰モデルの学習法の提案

[D-20-09]Evaluation of virtual sensing model interpretability based on anomaly detection and SHAP

[D-20-10]テーブルデータにおける入力空間の特徴を考慮したモデルベース反実仮想説明

[D-20-11]Model-based Reinforcement Learning by Predicting Various States through Latent Variable Editing