Deep learning (DL) plays an important role in modern agriculture, especially in plant
pathology using leaf images where convolutional neural networks (CNN) are attracting a lot …

This research aims to comprehensively analyze the most essential uses of artificial
intelligence in Aerospace Engineering. We obtained papers initially published in academic …

When detecting tomato leaf diseases in natural environments, factors such as changes in
lighting, occlusion, and the small size of leaf lesions pose challenges to detection accuracy …

Agriculture is a backbone for every nation. Farmers are facing a lot of problem to deal with
crop diseases, because crop diseases are bad for everyone involved farmers, consumers …

In natural environments, tomato leaf disease detection faces many challenges, such as
variations in light conditions, overlap** disease symptoms, tiny size of lesion areas, and …

Mango leaf diseases significantly threaten mango cultivation, impacting both yield and
quality. Accurate and early diagnosis is essential for effectively managing and controlling …

Tomato fungal diseases can cause significant economic losses to farmers. Advanced
disease detection methods based on symptom recognition in images face challenges when …

This study concentrates on the evaluation of apple quality, which is a vital part of the
agricultural industry. The quality of apples is examined through several factors, such as the …

UAV-based remote sensing combined with deep neural networks has recently emerged for
automated leaf disease detection on large-scale farmland. This research focuses on …

Within the domain of agricultural progress, accurately identifying instances of plant diseases
emerges as a pivotal hurdle. We introduce a fresh approach to classify diseases in maize …