The categorization and identification of agricultural imagery constitute the fundamental
requisites of contemporary farming practices. Among the various methods employed for …

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 …

Accurate weed detection is essential for precise weed control in farmland, and machine
vision serves as an effective method for identifying and targeting these unwanted plants. An …

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 …

Rumex obtusifolius Linnaeus (R. obtu. L.) is one of the vital broad-leaved weeds in
grassland that needs removal. It affects dairy products and reduces their quality. Hand …

With the growing technology and the use of the same in the field of farming, it is becoming
imperative that technology be used in the classification of crops and weeds as it is a growing …

Rice demand is increasing with the rise in population worldwide, but this crop production is
negatively affected due to different fatal diseases. Reported rice disease diagnosis models …

A crucial post-processing stage in numerous object detection methods is Non-Maximum
Suppression (NMS). The key idea of this technique is to rank the detected bounding boxes …

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 …

Distinguishing weeds from crops is a critical challenge in agriculture, with the existing
agriculture semantic segmentation networks simply combining low-level with high-level …