💻 Software & Environment Setup
Agriculture & Food Technology
The computational toolchain and environment used throughout AI for Crop Disease Detection using Hyperspectral and Drone Imaging.
Crop disease detection for PhD researchersDisease training for researchersImaging workshopDisease workshopCrop disease detection hands-on trainingCrop disease detection training India
# Recommended conda environmentconda create -n dstc_env python=3.11 -yconda activate dstc_envpip install rasterio geopandas scikit-learn xarrayGoogle Earth Engine
Remote-sensing crop analysis
Remote-sensing crop analysis
QGIS
Field mapping & spatial analysis
Field mapping & spatial analysis
R (agricolae)
Agronomic trial statistics
Agronomic trial statistics
scikit-learn
Yield & disease prediction models
Yield & disease prediction models
Supported OS: Linux (Ubuntu 22.04+), macOS, or Windows via WSL2.
Hardware: 16 GB RAM minimum; a CUDA GPU helps for deep-learning modules.
Earn government-registered certification in AI for Crop Disease Detection using Hyperspectral and Drone Imaging
e-Certificate and e-Marksheet issued on successful completion.
