Observe. Evaluate.
A peer-reviewed review of AI-driven crop disease detection and management.
Overview · Implementation · Evidence
01THE PUBLICATION
A Comprehensive Review of AI-Driven Approaches for Crop Disease Detection and Management
A survey of machine learning and deep learning approaches for crop disease identification, datasets, field deployment considerations and practical research challenges.
Authors Ojasvi Raj · Ankur Jain · Aryan Pahari · Nanda K · Anand Motwani · Ilma Khan
02WHY IT MATTERS
From models to the field
Practical ML requires more than predictive accuracy. Data quality, deployment context, and reproducibility shape whether research can translate into useful systems.
03READ THE PAPER
The original publication
The full publication, bibliography and verified citation are available through the DOI.