Image processing for agriculture.
By Laboratory of Field Phenomics, Graduate School of Agricultural and Life Sciences, The University of Tokyo.
Lab homepage
NOTE:
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)
Applications of Image analysis for agriculture.
資料Slides
Fundamentals of image analysis(Vectors and matrices operation)
Fundamentals of image analysis(Undstand Digital images and Preprocessing)
Image analysis for agriculture: Machine learning
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)
-
Study_CNN_Explainer (modified with weed dataset)
original version from Here: Zijie J. Wang et al., 2020.
Image analysis for agriculture: Multi-dimensional imaging
Data collection
- UAVPP, Breeder-Friendly-Plant-Phenotyping-tools for UAV, Wiki page.
- UGVPP, field phenotyping rover, homepage.
- 参考資料:
1.1 UAS-Based Plant Phenotyping for Research and Breeding Applications - 練習用データ:Sugarbeet_30m
- ソフトウェア:PREPs: Precision Plots Analyser for breeding field
- Dataset
1.1. Weed discrimination dataset
1.2. roboflowPublickDtaset - 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
2.2. Use Google colab
- Yann LeCun 深層学習コース(多言語資料あり)
- Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey
- 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)
- Youtube: Farmer live camera in 鹿児島
- Youtube:おすすめ深層学習入門動画(videos introduce Deep learning in Japanese)
- Youtube:The Future of Farming
- Youtube:Drones, robots, and super sperm – the future of farming
- 農林水産省:スマート農業
- 農林水産省:農業DX構想
- 九州大学3Dデジタル生物標本