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 …

In agriculture, crops are severely affected by illnesses, which reduce their production every
year. The detection of plant diseases during their initial stages is critical and thus needs to …

Classification and feature extraction are other planned areas of study, since they build upon
the basis of computer picture processing technology and have a direct impact on the results …

Benefits of independent learning and extraction of features have received a lot of attention in
recent years from both academic and professional circles. A subcategory of artificial …

This chapter highlights the importance of automated plant disease analysis for agricultural
enhancement. It addresses two critical challenges: disease identification and severity …

Plant disease management in agriculture science is the primary concern for every country,
as the food demand is increasing fast due to an increase in population. Furthermore …

Plant diseases have a significant impact on agricultural productivity and global food security.
Accurate and timely identification of plant diseases is crucial for effective disease …

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 …

In the field of artificial intelligence, deep learning is a sub-field. Automatic learning and
feature extraction have piqued the interest of academics and industry alike in recent years. It …

Deep learning is an artificial intelligence subfield. With the advantages of automated
learning and feature extraction, academic and industry circles have become increasingly …