In complex environments, overlapping leaves and uneven light can make pixels of leaf
edges difficult to identify, resulting in a poor segmentation performance of the target leaf. In …

The accurate segmentation of apple leaf disease spots is the key to identifying the
classification of apple leaf diseases and disease severity. Therefore, a DeepLabV3+ …

Research on the recognition and segmentation of vegetable diseases in simple
environments based on deep learning has achieved a relative success. However, in …

This paper discusses a sweetgum leaf-spot image segmentation method based on an
improved DeeplabV3+ network to address the low accuracy in plant leaf spot segmentation …

Tomato disease control is an urgent requirement in the field of intellectual agriculture, and
one of the keys to it is quantitative identification and precise segmentation of tomato leaf …

Identification technology of apple diseases is of great significance in improving production
efficiency and quality. This paper has used apple Alternaria blotch and brown spot disease …

Background Automatic and accurate estimation of disease severity is critical for disease
management and yield loss prediction. Conventional disease severity estimation is …

These are various critical aspects that limiting apple quality and productivity, the leaf disease
one of them. The usual examination process of leaf disease takes a lot of time to diagnose …

Accurate plant leaf image segmentation provides an effective basis for automatic leaf area
estimation, species identification, and plant disease and pest monitoring. In this paper …

Northern leaf blight (NLB) is a serious disease in maize which leads to significant yield
losses. Automatic and accurate methods of quantifying disease are crucial for disease …