Identifying and characterizing vascular plants in time and space is required in various
disciplines, eg in forestry, conservation and agriculture. Remote sensing emerged as a key …

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 …

Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …

This paper presents a comprehensive review of emerging technologies for the internet of
things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and …

The three previous industrial revolutions profoundly transformed agriculture industry from
indigenous farming to mechanized farming and recent precision agriculture. Industrial …

Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …

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 …

Investment in technological research is imperative to stimulate the development of
sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and …

Weeds are a crucial threat to agriculture, and in order to preserve crop productivity,
spreading agrochemicals is a common practice with a potential negative impact on the …

Automation in plant disease detection and diagnosis is one of the challenging research
areas that has gained significant attention in the agricultural sector. Traditional disease …