Background Weed recognition is key for automatic weeding, which is a challenging problem.
Weed recognition is mainly based on different features of crop images. The extracted image …

The accurate and rapid acquisition of crop and weed information is an important prerequisite
for automated weeding operations. This paper proposes the application of a network model …

Weed is a plant that grows along with nearly all field crops, including rice, wheat, cotton,
millets and sugar cane, affecting crop yield and quality. Classification and accurate …

Context Most weed species can adversely impact agricultural productivity by competing for
nutrients required by high-value crops. Manual weeding is not practical for large cropping …

Weeds are mainly spread by weed seeds being mixed with agricultural and forestry crop
seeds, grain, animal hair, and other plant products, and disturb the growing environment of …

Weeding is an effective way to increase crop yields. Reliable and accurate weed recognition
is a prerequisite for achieving high-precision site-specific weed control in precision …

Site-specific weed management in Precision Agriculture is becoming a popular topic among
researchers and farmers. The objective of this study was to classify weeds and crop species …

Weed identification is fundamental toward developing a deep learning-based weed control
system. Deep learning algorithms assist to build a weed detection model by using weed and …

Crop and weed discrimination in natural field environments is still challenging for
implementing automatic agricultural practices, such as weed control. Some weed control …

The maize field environment is complex. Weeds and maize have similar colors and may
overlap, and lighting and weather conditions vary. Thus, many methods for the automated …