Accurate and rapid plant disease detection is critical for enhancing long-term agricultural
yield. Disease infection poses the most significant challenge in crop production, potentially …

The notion of smart farming is gaining traction in the agricultural industry these days, and it
makes use of sensors and a variety of machine learning based technologies. According to …

INTRODUCTION: Deep Learning has significantly impacted various domains, including
medical imaging and diagnostics, by enabling accurate classification tasks. This research …

It is worth noting the fact that tea is the most popular drink on the planet and India is one of
the top producers and consumers of it. However, many diseases that affect crop quality and …

The paper aims to classify fruit leaf—disease pair using deep convolution neural network
(CNN) architecture. We have considered three fruits leaves ie, Apple, Custard apple and …

Rice sheath rot is a dangerous disease that affects rice crops all over the globe. It is
responsible for substantial yield losses and considerable economic damage. To effectively …

The agricultural sector faces several challenges in its efforts to increase its production. One
of the major challenges is diseases and insect pests that destroy plants and lead to a …

More than half of the people in the world rely on rice as their primary energy source. Two
main challenges in rice cultivation are plant diseases and nutrient deficiency. Brown spots …

Leaf abnormalities pose a significant threat to agricultural productivity, particularly in
medicinal plants such as Centella asiatica (Linn.) Urban (CAU), where they can severely …

In high milk yielding cattle udder and teat diseases are common. Due to this the farmers are
facing more problem in production and quality of milk. In agriculture, research of automatic …