ZaoShrubDL

Links to the code and data correspondig to the "Sub-alpine shrub classification using UAV images: Performance of human observers vs DL classifiers" paper in Ecological Informatics: https://www.sciencedirect.com/science/article/pii/S1574954124000049

Data

The Data used for the experiments in the paper is available in Zenodo:

LINK

Code

The code used in this paper was used to provide code examples in a drone image processing course. The following links correspond to the lessons of the course and include executable code in jupyter notebook format as well as written and video explanation about hot to use the code.

Pre-processing

Pre-processsing code, from mosaics to patches (course UNIT 3, Connected Components for patch extraction),

** Pre-processing VIDEO LESSON**

Dataset Handling

(Dataset Definition: (Course UNIT 4, Handling Custom Data in Pytorch),

**Dataset construction VIDEO LESSON**

Training DL networks

Training a ResNet Model (course UNIT 6, Training Deep Learning Models in Pytorch),

** Training a Resnet VIDEO LESSON**

Contact

The main page of the course contains the email address of one of the authors of the paper and person in charge of the drone image processing course who can be contacted to solve issues regarding the code.

General Course: https://colab.research.google.com/drive/1mjBugZmwa6OSxNaqkrCu4OCslKf2Wy7P?usp=sharing
Youtube Channel: https://www.youtube.com/channel/UCDxi6j88IlZXsRcAUXlscgw

• The Jupyter Notebooks for the code are also available in Japanese as units 3,4,5 of Course 4 in https://colab.research.google.com/drive/1wYIcjC74RnB3HcpqCWWoXLUjVlD8N1YU?usp=sharing　　
• コードのJupyter Notebook は、次のリンクの４番目のコース、ユニット 3、4、5 として日本語でも入手できます。https://colab.research.google.com/drive/1wYIcjC74RnB3HcpqCWWoXLUjVlD8N1YU?usp=sharing