Crop disease detection is important due to its significant impact on agricultural productivity
and global food security. Traditional disease detection methods often rely on labour …

Considering the high requirements of current kiwifruit picking recognition systems for mobile
devices, including the small number of available features for image targets and small-scale …

The fungal disease known as cucumber leaf spot (CLS) is capable of causing substantial
damage to cucumber crops, leading to a decrease in production and quality. Early detection …

Tea sprout segmentation and picking point localization via machine vision are the core
technologies of automatic tea picking. This study proposes a method of tea segmentation …

Automation of agriculture with the use of cutting-edge technology is a growing research
area. It addresses the issue of better yields and tries to mitigate the negative impact due to …

We propose a lightweight neural network-based method to detect the estrus behavior of
ewes. Our suggested method is mainly proposed to solve the problem of not being able to …

Introduction Current detection methods for apple leaf diseases still suffer some challenges,
such as the high number of parameters, low detection speed and poor detection …

This research evaluates 20 advanced convolutional neural network (CNN) architectures for
classifying mushroom diseases in Agaricus bisporus, utilizing a custom dataset of 3195 …

BACKGROUND With the rapid development of deep learning, the recognition of rice disease
images using deep neural networks has become a hot research topic. However, most …

The abstract functions as a succinct summary of the main conclusions drawn from the study.
By utilizing the extensive classification performance metrics shown in the attached table, the …