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 precision spraying robot dispensing herbicides only on unwanted plants based on
machine vision detection is the most appropriate approach to ensure the sustainable agro …

Automatic detection of plant diseases has emerged as a challenging field in the last decade.
Computer vision-based advancements have helped in the timely and accurate identification …

This study aimed to address the problems of low detection accuracy and inaccurate
positioning of small-object detection in remote sensing images. An improved architecture …

Weeds pose a serious production challenge in various agronomic crops by reducing their
grain yields. Increasing cases of herbicide-resistant (HR) weed populations further …

Weeds can decrease yields and the quality of crops. Detection, localisation, and
classification of weeds in crops are crucial for develo** efficient weed control and …

Semantic segmentation has been widely used in precision agriculture, such as weed
detection, which is pivotal to increasing crop yields. Various well-established and swiftly …

Due to the massive surge in the world population, the agriculture cycle expansion is
necessary to accommodate the anticipated demand. However, this expansion is challenged …

Weeds are unwanted and invasive plants that proliferate and compete for resources such as
space, water, nutrients, and sunlight, affecting the quality and productivity of the desired …

The natural environment in which field soybeans are grown is complex in terms of weed
species and distribution, and a wide range of weeds are mixed with soybeans, resulting in …