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日時:2019 年5 月14 日(火) 場所:東京大学農学生命科学研究科

Useful information part 1 (overview)

  1. 渡辺翔, 郭威(2018). イメージセンシングで植物を測ろう―導入から解析まで―. 育種学研究, 2018年20巻1号, 64-68.
  2. 郭威, 渡辺翔,  伊藤淳士(2018). ドローン画像解析による圃場高速フィールドフェノタイピングのための要素技術. アグリバイオ, 2018年第2巻3号, 8-13.

Useful information part 2 (what to measure?)

  1. Chapman, S.C., Zheng, B., Potgieter, A., Guo, W., Baret, F., Liu, S., Madec, S., Solan, B., George-Jaeggli, B., Hammer, G., Jordan, D.(2018). Visible, near infrared, and thermal spectral radiance on-board UAVs for high throughput phenotyping of plant breeding trials. In Thenkabail, P.S., Lyon, J.G., Huete, A.(Eds.). Vol(3),Biophysical and Biochemical Characterization and Plant Species Studies. Hyperspectral Remote Sensing of Vegetation, Second Edition, Four Volume, CRC Press. ISBN 9781138066250. Charpter available here
  2. PrecisionMapper; Sensefly

Useful information part 3 (how to measure?)

  1. Video at Youtube: Part of today's lecture contents (machine learing and image processing):
    Guo, W.(2019). Easy Plant Phenotyping by using Image processing and machine learning techniques, January 24, 2019, IPPN Imaging Workgroup Webinars

Useful information part 4 (Tools and documents?)

  1. UAVPP, Breeder-Friendly-Plant-Phenotyping-tools for UAV, Wiki page
  2. How to use python easliy, Install Anaconda and opencv, document
  3. How to segment crop(or any targets) from background:
    1. Threshold based method: opencv tutorial
    2. Machine learning based method: EasyPCC_V2, source code & software
  4. 自律移動のプロセス 日本語解釈


Wei GUO (Oceam), 東京大学国際フィールドフェノミクス研究拠点
International Field Phenomics Research Laboratory, The University of Tokyo, Tokyo, Japan

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