Plant pathogens can decimate crops and render the local cultivation of a species
unprofitable. In extreme cases this has caused famine and economic collapse. Timing is vital …

As advancements in agricultural technology unfold, machine learning and deep learning
approaches are gaining interest in robust plant disease identification. Early disease …

Agriculture has undergone a remarkable transformation, transitioning from traditional
methods that were used for centuries to technology-driven practices. The advent of image …

Efficient and rational monitoring of plant health is an essential prerequisite for ensuring
optimal crop production and resource management in the field of agriculture. Computer …

Plant disease detection has played a significant role in combating plant diseases that pose a
threat to global agriculture and food security. Detecting these diseases early can help …

Insects and illnesses that affect plants can have a major negative effect on both their quality
and their yield. Digital image processing may be applied to diagnose plant illnesses and …

Deep learning techniques, and in particular Convolutional Neural Networks (CNNs), have
led to significant progress in image processing. Since 2016, many applications for the …

Diagnosing plant diseases is a challenging task due to the complex nature of plants and the
visual similarities among different species. Timely identification and classification of these …

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 …

India loses 35% of the annual crop yield due to plant diseases. Early detection of plant
diseases remains difficult due to the lack of lab infrastructure and expertise. In this paper, we …