Several factors associated with disease diagnosis in plants using deep learning techniques
must be considered to develop a robust system for accurate disease management. A …

Plant diseases and pests are important factors determining the yield and quality of plants.
Plant diseases and pests identification can be carried out by means of digital image …

Globally, all the major crops are significantly affected by diseases every year, as manual
inspection across diverse fields is time-consuming, tedious, and requires expert knowledge …

Crop diseases cause a substantial loss in the quantum and quality of agricultural production.
Regular monitoring may help in early stage disease detection an d thereby reduction in crop …

Investment in technological research is imperative to stimulate the development of
sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and …

Fast and accurate plant disease detection is critical to increasing agricultural productivity in
a sustainable way. Traditionally, human experts have been relied upon to diagnose …

Internet of things (IoT) is a promising technology which provides efficient and reliable
solutions towards the modernization of several domains. IoT based solutions are being …

Food security for the 7 billion people on earth requires minimizing crop damage by timely
detection of diseases. Most deep learning models for automated detection of diseases in …

Plant diseases are the primary cause of crop losses globally, which have an impact on the
world economy. To deal with these issues, new agriculture solutions are evolving that …

Biotic stress consists of damage to plants through other living organisms. The efficient
control of biotic agents such as pests and pathogens (viruses, fungi, bacteria, etc.) is closely …