Deep learning constitutes a recent, modern technique for image processing and data
analysis, with promising results and large potential. As deep learning has been successfully …

Plant diseases affect the growth of their respective species, therefore their early identification
is very important. Many Machine Learning (ML) models have been employed for the …

Weeds are among the major factors that could harm crop yield. With the advances in
electronic and information technologies, machine vision combined with image processing …

Weeds are one of the most important factors affecting agricultural production. The waste and
pollution of farmland ecological environment caused by full-coverage chemical herbicide …

The agriculture industry is undergoing a rapid digital transformation and is growing powerful
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …

Precision farming robots, which target to reduce the amount of herbicides that need to be
brought out in the fields, must have the ability to identify crops and weeds in real time to …

Robotic weed control has seen increased research of late with its potential for boosting
productivity in agriculture. Majority of works focus on develo** robotics for croplands …

This paper studies convolutional neural networks (CNN) to learn unsupervised feature
representations for 44 different plant species, collected at the Royal Botanic Gardens, Kew …

Agriculture is the basis of every economy worldwide. Crop production is one of the major
factors affecting domestic market condition in any country. Agricultural production is also a …

Plant identification systems developed by computer vision researchers have helped
botanists to recognize and identify unknown plant species more rapidly. Hitherto, numerous …