The rapid advances in Deep Learning (DL) techniques have enabled rapid detection,
localisation, and recognition of objects from images or videos. DL techniques are now being …

Deep Learning (DL) has been described as one of the key subfields of Artificial Intelligence
(AI) that is transforming weed detection for site-specific weed management (SSWM). In the …

Blockchain quickly became an important technology in many applications of precision
agriculture discipline. The need to develop smart P2P systems capable of verifying …

Alternative non-chemical or chemical-reduced weed control tactics are critical for future
integrated weed management, especially for herbicide-resistant weeds. Through weed …

In this paper we address the problem of recognising the Broad-leaved dock (Rumex
obtusifolius L.) in grasslands from high-resolution 2D images. We discuss and present the …

Accurate classification of weed species in crop plants plays a crucial role in precision
agriculture by enabling targeted treatment. Recent studies show that artificial intelligence …

Recent computer vision techniques based on convolutional neural networks (CNNs) are
considered state-of-the-art tools in weed map**. However, their performance has been …

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 …

Accurately detecting early developmental stages of insect pests (larvae) from off-the-shelf
stereo camera sensor data using deep learning holds several benefits for farmers, from …

Monitoring climate conditions has continuously gained much attention in recent times due to
the dynamism associated with weather across different agricultural jurisdictions. There are …