Weeds and crops engage in a relentless battle for the same resources, leading to potential
reductions in crop yields and increased agricultural costs. Traditional methods of weed …

Weeds are a significant threat to agricultural productivity and the environment. The
increasing demand for sustainable weed control practices has driven innovative …

Abstract Machine learning and deep learning are subsets of Artificial Intelligence that have
revolutionized object detection and classification in images or videos. This technology plays …

Weeds were one of the most destructive constraints on crop production and posed a
significant threat to agricultural productivity. The increasing development of smart agriculture …

In the face of increasing agricultural demands and environmental concerns, the effective
management of weeds presents a pressing challenge in modern agriculture. Weeds not only …

Controlling weed infestation through chemicals (herbicides & pesticides) is essential for crop
yield. However, excessive use of these chemicals has caused severe agronomic and …

Weed management is a crucial aspect of crop production that requires significant effort, time,
and resources. Traditional weed management methods involve the use of herbicides and …

In the next three decades, crop production must be doubled as the population is likely to
increase by 35 percent. To enhance crop production to a great extent, the issues behind the …

Agriculture has been completely transformed by Deep Learning (DL) techniques, which
allow for quick object localization and detection. However, because weeds and crops are …

The main objective of this study is to develop a method for the automated detection and
classification of weeds and sugar beets. Precision agriculture is an essential area of …