S Umamaheswari, R Arjun… - 2018 Conference on …, 2018 - ieeexplore.ieee.org
Human community are educated about the environmental issues of pesticides and fertilizers used in agriculture. There is a ever-growing demand for food to be met by agriculture …
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 …
Weeds are a significant threat to agricultural productivity and the environment. The increasing demand for sustainable weed control practices has driven innovative …
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 …
Y Subbarayudu, A Soppadandi… - E3S Web of …, 2023 - e3s-conferences.org
Weeds are a major threat to crops, making early detection critical for maintaining agricultural productivity. Weeds are generally toxic, equipped with thorns and burrs, and can disrupt …
X Jin, J Che, Y Chen - IEEE access, 2021 - ieeexplore.ieee.org
Weed identification in vegetable plantation is more challenging than crop weed identification due to their random plant spacing. So far, little work has been found on identifying weeds in …
Weeds are aggressive, computing for light, water, nutrients and space for crops, garden plants or lawn grass. Management of weeds usually consists of spraying herbicides in the …
Weeds are one of the most harmful agricultural pests that have a significant impact on crops. Weeds are responsible for higher production costs due to crop waste and have a significant …
In modern agriculture, there are many technologies that improve the performance of farming and production of the main plant. Few such important technologies are the machine learning …