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 …

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 …

In recent years, weeds have been responsible for most agricultural yield losses. To deal with
this threat, farmers resort to spraying the fields uniformly with herbicides. This method not …

Weed detection is still a challenging problem for robotic weed removal. Small tolerance
between the cutting tine and main crop position requires highly precise discrimination of the …

Weeds are harmful to crop yield. The segmentation of weeds in images is of great
significance for precise weeding and reducing herbicide pollution. However, in the field …

Weed suppression is an important factor affecting crop yields. Precise identification of weed
species will contribute to automatic weeding by applying proper herbicides, hoeing position …

Highlights•We processed the snapshot mosaic hyperspectral images.•Grid search approach
was used to optimise the hyper-parameters of the Random Forests.•Cross validation was …

Highlights•Transfer learning provided very promising performance for weed/crop
classification.•The highest classification accuracy of 98.7% was obtained with VGG-19.•All …

Highlights•The potential of wavelet texture features in crop-weed discrimination was
examined.•From wavelet multi-resolution images, 52 texture features were extracted.•Image …

Abstract Machine vision-based precision herbicide application in wheat (Triticum aestivum
L.) can substantially reduce herbicide input. However, detecting newly emerged weeds in …