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agri-image's Introduction

agri-image

Image processing for agriculture.
By Laboratory of Field Phenomics, Graduate School of Agricultural and Life Sciences, The University of Tokyo.
Lab homepage
NOTE:

事前準備(Preparation)

なぜGooglecolab?
Pythonの環境構築不要なGPUも使えるWebサービス(基本無料)

植物画像データに基づくデータ解析の応用例.

Applications of Image analysis for agriculture.
資料Slides

植物画像データの画像解析(1)

Fundamentals of image analysis(Vectors and matrices operation)

  1. Googlecolab_fundamentals_1
    image
  2. Googlecolab_fundamentals_2
    image

植物画像データの画像解析(2)

Fundamentals of image analysis(Undstand Digital images and Preprocessing)

  1. Googlecolab_fundamentals_3
    image
  2. Googlecolab_fundamentals_4
    image
  3. Googlecolab_fundamentals_5
    image

植物画像データの機械学習

Image analysis for agriculture: Machine learning
image

植物画像データの深層学習

Image analysis for agriculture: Deep learning
Demo1:
Example:雑草識別モデル (Weed recognization demo)
Demo2:
Example:ムギ穂検出モデル(wheat head detection)

  1. Study_CNN_Explainer (modified with weed dataset)
    original version from Here: Zijie J. Wang et al., 2020.

  2. 初心者のための TensorFlow 2.0 入門

  3. 畳み込みニューラルネットワーク (Convolutional Neural Networks)

  4. TensorFlow2 for beginner
    image

  5. Image classification
    image

  6. Object detection
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  7. Semantic segmentation
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多次元画像データの解析(三次元点群中心)

Image analysis for agriculture: Multi-dimensional imaging
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植物画像データの収集.

Data collection

  1. UAVPP, Breeder-Friendly-Plant-Phenotyping-tools for UAV, Wiki page.  
  2. UGVPP, field phenotyping rover, homepage.

ドローン画像解析:  

  1. 参考資料:
    1.1 UAS-Based Plant Phenotyping for Research and Breeding Applications
  2. 練習用データ:Sugarbeet_30m
  3. ソフトウェア:PREPs: Precision Plots Analyser for breeding field

深層学習を実践する

  1. Dataset
    1.1. Weed discrimination dataset
    1.2. roboflowPublickDtaset
  2. Try playing with weed discrimination model(Classification)
    2.1. Use Google Teachable Machine
    2.1.1 Try to use the model made from Google Teachable machine
    image
    2.2. Use Google colab
    image
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Useful information

  1. Yann LeCun 深層学習コース(多言語資料あり)
  2. Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey
  3. AIセミナー"深層学習を使ったキュウリ選別機つくってみた" (a farmer made his own Cucumber ranking machine)
  4. Youtube: Farmer live camera in 鹿児島
  5. Youtube:おすすめ深層学習入門動画(videos introduce Deep learning in Japanese)
  6. Youtube:The Future of Farming
  7. Youtube:Drones, robots, and super sperm – the future of farming
  8. 農林水産省:スマート農業
  9. 農林水産省:農業DX構想
  10. 九州大学3Dデジタル生物標本

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Contributors

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