DETECTION AND CLASSIFICATION OF DISEASES OF CASSAVA LEAVES: USING DEEP NEURAL NETWORKS WITH OPTIMIZATION ALGORITHMS

Cassava stands as a vital staple crop and the most significant source of starch globally, playing a fundamental role in ensuring food security and providing income for millions of people, particularly within developing nations. Ranked as the fifth most cultivated staple food crop in the world, cassava is distinguished by its robust adaptability to diverse soil types and harsh environmental conditions. However, both agricultural productivity and farmer livelihoods face severe threats from the proliferation of diseases, including cassava mosaic disease (CMD), cassava brown streak disease (CBSD), cassava green mottle (CGM), and cassava bacterial blight (CBB).Traditional disease diagnosis remains heavily reliant on manual visual inspections conducted by specialists—a method that is not only time-consuming and subjective but also significantly limited by the scarcity of skilled plant pathologists in many regions. In this context, the development of automated and reliable methods for identifying cassava diseases has become an urgent necessity.This book introduces advanced methodologies utilizing Deep Neural Networks integrated with optimization algorithms.