The ‘AgriHub,’ Innovation Hub for Agriculture at the Indian Institute of Technology Indore, is emerging as a major centre for AI-based agricultural innovation in India. Inaugurated on January 27, 2025 ...

An unusually mild winter followed by a wet spring made last year one of the worst in a decade for Pennsylvania soybean ...

Investigators developed and validated a masked autoencoder deep learning model using vision transformer technology to automate the detection and grading of nuclear cataracts from slit-lamp images.

Cellar Insights deploys potato storage technology using wireless sensors and machine learning to cut post-harvest losses for ...

This repository contains the source code for an automated crop disease identification system developed as part of my Final Year Project (FYP). The system is designed to assist the Malaysian ...

Farmers have long fought a quiet war against the fungi that rot crops in fields and storage sheds. Each year, these diseases destroy harvests of lettuce, beans, oilseed rape, wheat, and many other ...

Crop Disease Detection using Machine Learning is a CNN-based system that identifies crop diseases from leaf images and provides preventive measures, helping farmers detect diseases early and reduce ...

Abstract: Precisely identifying crop diseases is a key to achieving high agricultural productivity as well as reduction of agricultural yield losses. Conventional practices in detection of crop ...

Abstract: Artificial Intelligence (AI) has become a vital tool for agricultural farming. AI-based image processing models utilizing different machine learning (ML) algorithms and deep learning (DL) ...

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...