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Unsupervised Defect Detection for Automatic Shiitake Sorting 査読あり
Nokura S., Kimura L., Ishimaru T., Oshikawa Y., Ikeda S., Aoki K., Ohe K., Takei A., Kawamura R., Sakamoto M., Sugimoto K.
Proceedings of International Conference on Artificial Life and Robotics 430 - 433 2026年
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス） 出版者・発行元：Proceedings of International Conference on Artificial Life and Robotics
Automated shiitake sorting faces severe data imbalance (1,731 good vs. 241 defective images) and annotation difficulties. We compared data augmentation and unsupervised detection. First, augmenting scarce defective data with GANs failed; models either lost subtle defect features (e.g., discoloration) during pre-processing or overfit to augmentation patterns, proving label-less augmentation difficult. We then shifted to unsupervised anomaly detection (VAE+OC-SVM) trained only on good data. This model achieved perfect Recall (100%) for the defective class, identifying all bad items without a single miss. This Recall 100% capability demonstrates its high practical utility as a primary screening tool for quality control, particularly where preventing defective product leakage is prioritized (albeit with low precision). This approach highlights a path for automated sorting in data-scarce agricultural settings and suggests high transferability to other products (e.g., tomato, potato) with similar data constraints.
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Broadening Access-to Creative Experience with MR 3D Painting 査読あり
Ishimaru T., Oshikawa Y., Nokura S., Ikeda S., Aoki K., Ohe K., Takei A., Kawamura R., Sakamoto M.
Proceedings of International Conference on Artificial Life and Robotics 421 - 425 2026年
掲載種別：研究論文（学術雑誌） 出版者・発行元：Proceedings of International Conference on Artificial Life and Robotics
Access to arts experiences varies by income and locality, creating an experience divide. We present a low-barrier mixed-reality (MR) 3D-painting system on Meta Quest 3 that renders strokes in the user's surrounding space in passthrough MR. We conducted two complementary studies: an in-the-wild festival study with local children (MR 3D free creation) and a controlled study with university students enabling within-participant comparisons across free 2D drawing, free 3D drawing (with depth), and prompted 3D drawing. After each condition, participants rated immersion, accomplishment, perceived creativity, self-efficacy, intention to continue, and usability (plus two free-creation items) on 5-point Likert scales, and collaboration was assessed in paired tasks. We report condition-wise medians and within-participant median differences. Results suggest that MR can deliver meaningful creative experiences with minimal setup in everyday spaces and inform how task framing supports depth-oriented 3D creation.
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Proposal of a Muscle Training Method using EMG Visualization via Machine Learning 査読あり
Oshikawa Y., Ishimaru T., Nokura S., Ikeda S., Aoki K., Ohe K., Takei A., Kawamura R., Sakamoto M.
Proceedings of International Conference on Artificial Life and Robotics 426 - 429 2026年
掲載種別：研究論文（学術雑誌） 出版者・発行元：Proceedings of International Conference on Artificial Life and Robotics
Strength training is essential for maintaining health and building an attractive physique, yet many people struggle to stick with it. One reason for this is that they fail to feel the effects of strength training. To maximize the effects of strength training, mastering proper form is essential. Therefore, I embarked on this research to reduce the number of people who quit strength training by visualizing muscle load in real time during workouts.We are developing a system that uses machine learning to visualize muscle load from user form, enabling muscle load visualization without requiring electromyography. At present, it is possible to estimate muscle load, but the accuracy of this estimation is low. Therefore, we are currently experimenting to improve the accuracy of muscle load estimation.
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Development of a Crisis-Avoidance Simulator Based on the Boids Model 査読あり
Hidaka T., Sakamoto M., Aoki K.
Proceedings of International Conference on Artificial Life and Robotics 444 - 447 2026年
掲載種別：研究論文（学術雑誌） 出版者・発行元：Proceedings of International Conference on Artificial Life and Robotics
This study presents the development of a crisis-avoidance simulator based on Reynolds' Boids model, designed to simulate crowd escape behavior in two-dimensional environments during attack scenarios. The simulator incorporated structural elements such as openings, wall-induced reflection and repulsion, and line-of-sight occlusion. It featured a single attacker who pursued the nearest visible agent (boid) and multiple agents who attempted to flee. Simulation experiments under various room configurations revealed that spatial structures and inter-agent interactions significantly influenced escape dynamics. These findings suggest that the proposed simulator could serve as a valuable tool for optimizing evacuation route design and emergency behavior planning.
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Pongpiyapaiboon S., Aoki K., Hashiguchi M., Akashi R., Kishima Y., Tanaka H.
Plant Phenome Journal 8 ( 1 ) 2025年12月
掲載種別：研究論文（学術雑誌） 出版者・発行元：Plant Phenome Journal
High-throughput and noninvasive phenotyping methods are promising technology for improving efficiency in plant research and breeding. In this study, we evaluated the performance of a digital phenotyping system (DPS) based on three-dimensional (3D) model reconstruction for quantifying key growth traits in rice (Oryza sativa). The DPS was used to estimate plant height, biomass, color, leaf morphology, and tiller angle in four rice varieties (Koshihikari, Nipponbare, PL9, and Tachiaoba). The results show high accuracy and correlation between manually measured and DPS-derived traits. Notably, the 3D volume analysis can quantify biomass accumulation and growth dynamics and revealed distinct differences among varieties. The strong correlation between the green-red normalized difference index (a red-green-blue-based index) and soil plant analysis development also demonstrated the viability of the system in monitoring leaf color without using a multispectral instrument. The analysis also captured growth patterns over time, including canopy development and senescence, which are often challenging to quantify through manual measurements alone. Furthermore, the tiller angle estimation derived from DPS provided an alternative method to plant architecture evaluation, demonstrating its potential for use in breeding programs aimed to optimize canopy structure. These findings establish DPS as a reliable and scalable tool for a digital phenotyping platform that enables comprehensive trait analysis with reduced labor and increased precision and the capability to continuously monitor plant growth and biomass accumulation. This study shows the potential of this novel digital tool for automating manual measurements, which can increase efficiency and expedite research and breeding in rice and other crops.
DOI： 10.1002/ppj2.70054
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オンデマンド授業のための高画質コンテンツの作成と評価－高等教育における試み－
青木 謙二
メディア教育研究 Vol.1, No.2, p.91-101 2005年
記述言語：日本語 掲載種別：記事・総説・解説・論説等（大学・研究所紀要）
講演・口頭発表等 【 表示 ／ 非表示 】
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無線LANのセッションログによるデバイス移動情報の可視化の試み
林田 雄成、青木 謙二
情報処理学会IOT研究会 2024年9月19日
開催年月日： 2024年9月19日 - 2024年9月20日
会議種別：口頭発表（一般）
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情報セキュリティ対策自己診断システムを用いた自己診断結果の分析
青木謙二, 園田誠, 黒木亘, 宮本理司, 廿日出勇
大学ICT推進協議会2023年度年次大会 2023年12月15日
開催年月日： 2023年12月13日 - 2023年12月15日
記述言語：日本語 会議種別：口頭発表（一般）
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情報セキュリティ対策自己診断システムを用いた自己診断結果の分析
黒木 亘, 廿日出 勇, 宮本 理司, 青木 謙二, 園田 誠
大学ICT推進協議会年次大会論文集 2023年12月6日 一般社団法人 大学ICT推進協議会
開催年月日： 2023年12月6日
記述言語：日本語 会議種別：口頭発表（一般）
本学では、より簡単に自身が管理するPCの情報セキュリティ対策の状況を把握するために自己診断システムを構築し、これを用いた自己点検を2022年度から実施してきた。本論文では、2022年度と2023年度の約2年間の実施状況を確認し、その結果を年度間で比較し、変化がみられるかを分析した。この結果、2022年度に自己診断を行った者の総数は1,390名、PCの総数は1,456台で、2023年度に自己診断を行った者の総数は1,164名、PCの総数は1,273台と毎年度、同程度数の教職員、学生が、同程度数のPCに対して自己点検を実施していることがわかった。また、年度によらず、30%程度のPCでウイルス対策ソフトのスキャン実施とスクリーンロックの実施が行われておらず、他の診断項目よりも特に実施状況が悪いことがわかった。さらに、2022年度に診断結果が正常となったPCであっても、2023年度の初回診断では異常と診断されるPCが35％あり、一旦、情報セキュリティ対策が行われたとしても、その後の情報セキュリティ対策が維持できていないことが示唆された。
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CNNによる渦巻き錯視の認識
東郷拓弥、坂本眞人、青木謙二
2022年度 電気・情報関係学会九州支部連合大会 2022年9月17日
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コロナ禍におけるオンライン授業の実践
青木 謙二
第2９回 国公立大学情報システム研究会総会 2021年3月5日