未分類

TAKAHASHI Ryo (B4), KOBAYASHI Taketo (M2), TAMURA Shun (B4), ISOBE Daisuke (B4), MORITAKE Katsuhito (M2)
INOUE Daisuke (M2), DOHI Ayuna (B4), MAO Xiaoyang (Professor), BUAYAI Prawit (Assistant Professor), WOO Yan San (M2)

To appear: SHANMUGANATHAN Meerahshvin (M2), FUJISAWA Shunsuke (B4)

ブドウの粒を数えるスマートグラス／茅暁陽（山梨大学 工学部 教授）
Available before: 23:05, 20th Oct.
Video

Event: Japanese Society of Public Health 2022 (in Japanese)

Exhibition period: 10/7 to 10/9

Demonstration period: 10/7 to 10/8

Demonstrator: Daisuke Inoue, Taketo Kobayashi, Katsuhito Moritake

Ligeng Chen, Zhenyang Zhu, Kentaro Go, Wangkang Huang, Xiaoyang Mao, “Swin Transformerを利用した色覚障がい支援用色変換手法”, Visual Computing シンポジウム, Article 41, 2022-10.

石川 直彦, 朱 臻陽, 茅 暁陽, “知覚サイズを反映した写真生成のための画像自動部分拡大方法”, Visual Computing シンポジウム, Article 42, 2022-10.

Kaishi Naito, Daisuke Inoue, Prawit Buayai, and Xiaoyang Mao, “A Pilot Study on the AR Interface Design for People with Intellectual Disabilities”, Cyberworlds, 2022. Cyberworlds 2022

戦略的スマート農業技術等の開発・改良事業「AI 駆動型栽培体系：人間とロボットの協働によるシャインマスカット栽培の高効率・高品質化」のキックオフミーティングを開催！

令和4年7月6日（水）、甲府キャンパスにおいて、戦略的スマート農業技術等の開発・改良事業「AI 駆動型栽培体系：人間とロボットの協働によるシャインマスカット栽培の高効率・高品質化」のキックオフミーティングを開催しました。[詳細]

Sorry, this entry is only available in 日本語.

The research group led by Professor Xiaoyang Mao at department of computer science and engineering, faculty of engineering, University of Yamanashi, developed new a berry counting AI technique for berry thinning, which can be executed on smart phone in real-time. [More]

Research paper, entitled “Image Recoloring for Red-Green Dichromats with Compensation Range based Naturalness Preservation and Refined Dichromacy Gamut”, was accepted by Computer Graphics International 2022 (CGI2022) (accepted paper will be published on the international journal The Visual Computer (IF: 2.601(2022)))

Shota Chi, a fourth-year bachelor’s student at the Professor Mao Laboratory at the University of Yamanashi, received the Student Encouragement Award at the 84rd IPSJ National Convention for his research “Automatic Prediction for Meat Cooking using Deep Learning.”

Following the study on grape, we will conduct empirical research on Lemon Cultivation using Artificial Intelligence (AI) and Augmented-Reality (AR) techniques.

We will continuously engage in study on compensation for people with color vision deficiency based on the latest techniques of Deep Learning (DL) and Augmented-Reality (AR).

Paper “Generative Data Augmentation for Automatic Meter Reading Using CNNs” has been accepted by IEEE Access journal (IF: 3.367(2020)).