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 …

Computer vision (CV) combined with a deep convolutional neural network (CNN) has
emerged as a reliable analytical method to effectively characterize and quantify high …

The deep learning methods based on convolutional neural network (CNN) have been
widely explored in dataset augmentation and recognition of plant leaf diseases. The recently …

Grape black measles disease may be one of the best known, longest studied and most
destructive of all plant diseases, which ultimately reduces productivity and quality of …

Tomato leaf infections are a common threat to long-term tomato production that affects many
farmers worldwide. Early detection, treatment, and solution of tomato leaf specificity are …

Disease has a significant impact on strawberry quality and yield, and deep learning has
become an important approach for the detection of crop disease. To address the problems of …

Plant diseases are the main factors affecting the agricultural production. At present,
improving the efficiency of plant disease identification in natural scenarios is a crucial issue …

Cassava is a crucial food and nutrition security crop cultivated by small-scale farmers and it
can survive in a brutal environment. It is a significant source of carbohydrates in African …

Leaf spot disease, which causes 10− 50% loss in sugar beet yield, causes great damage on
the leaves. This disease physiologically appears as individual circular spots on the sugar …

Accurate detection of plant leaves is a meaningful and challenging task for developing smart
agricultural systems. To improve the performance of detecting plant leaves in natural scenes …