Rapid improvements in deep learning (DL) techniques have made it possible to detect and
recognize objects from images. DL approaches have recently entered various agricultural …

Plant diseases can significantly reduce crop yield and product quality. Visual inspections of
plants by human observers for disease identification are time-consuming, costly, and prone …

Abstract Internet of Things (IoT) frameworks generates data for large and remote agricultural
areas through sensors and use this data for crop predictions by several machine learning …

Apple disease is one of the major factors affecting apple production, and the visual
diagnosis of apple leaves is an efficient disease identification solution. In this paper, we …

Convolutional neural networks (CNNs) have the potential to enable a revolution in
bioacoustics, allowing robust detection and classification of marine sound sources. As …

Corn plants are classified based on the leaf as healthy leafy and have 3 types of diseases
leaf namely northern leaf blight, common rust, and gray leaf spot. Convolutional neural …

This paper presents the development of a robotic sprayer that combines artificial intelligence
with robotics for optimal spray application on citrus nursery plants grown in an indoor …

Due to the increase in human population, the need for food crops is also increasing day by
day. In each year, 10 to 30% agricultural yield is lost due to the attack of pests and various …

Globally, tea production and its quality fundamentally depend on tea leaves, which are
susceptible to invasion by pathogenic organisms. Precise and early-stage identification of …

Tomatoes are the most widely grown vegetable, used in a wide variety of dishes around the
world. After potatoes and sweet potatoes, it is the third most extensively cultivated crop in the …