As compared with the traditional visual discrimination methods, deep learning and image
processing methods have the ability to detect plants efficiently and non-invasively. This is of …

Brown blight, target spot, and tea coal diseases are three major leaf diseases of tea plants,
and Apolygus lucorum is a major pest in tea plantations. The traditional symptom recognition …

Stress due to nutrients deficiency in plants can reduce the agricultural yield significantly.
Nitrogen, an essential nutrient, is a crucial growth-limiting factor and is the prime component …

Plant stress is one of major issues that cause significant economic loss for growers. The
labor-intensive conventional methods for identifying the stressed plants constrain their …

A compelling effort has been made in recent years to face several kinds of plant stresses
using a variety of sensors and deep learning methods. Yet most of the datasets are based …

Recent technological developments in the primary sector and machine learning algorithms
allow the combined application of many promising solutions in precision agriculture. For …

The biggest challenge in the classification of plant water stress conditions is the similar
appearance of different stress conditions. We introduce HortNet417v1 with 417 layers for …

CONTEXT Paddy crop stress can significantly reduce the quality and quantity of agricultural
goods and severely affect food production safety. Untimely stress and inaccurate crop …

The accurate detection and identification of tea leaf diseases are conducive to its precise
prevention and control. Convolutional neural network (CNN) can automatically extract the …

Recent years have seen an increased effort in the detection of plant stresses and diseases
using non-invasive sensors and deep learning methods. Nonetheless, no studies have been …