Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
The digitalization of data has resulted in a data tsunami in practically every industry of data-
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …
driven enterprise. Furthermore, man-to-machine (M2M) digital data handling has …
A survey of deep learning techniques for weed detection from images
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 …
localisation, and recognition of objects from images or videos. DL techniques are now being …
[HTML][HTML] A review of applications and communication technologies for internet of things (Iot) and unmanned aerial vehicle (uav) based sustainable smart farming
To reach the goal of sustainable agriculture, smart farming is taking advantage of the
Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) paradigm. These smart farms …
Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) paradigm. These smart farms …
[HTML][HTML] Automation and digitization of agriculture using artificial intelligence and internet of things
The growing population and effect of climate change have put a huge responsibility on the
agriculture sector to increase food-grain production and productivity. In most of the countries …
agriculture sector to increase food-grain production and productivity. In most of the countries …
[HTML][HTML] Early weed detection using image processing and machine learning techniques in an Australian chilli farm
This paper explores the potential of machine learning algorithms for weed and crop
classification from UAV images. The identification of weeds in crops is a challenging task …
classification from UAV images. The identification of weeds in crops is a challenging task …
Machine learning for smart agriculture and precision farming: towards making the fields talk
In almost every sector, data-driven business, the digitization of the data has generated a
data tsunami. In addition, man-to-machine digital data handling has magnified the …
data tsunami. In addition, man-to-machine digital data handling has magnified the …
[HTML][HTML] Metaheuristic optimization for improving weed detection in wheat images captured by drones
Background and aim: Machine learning methods are examined by many researchers to
identify weeds in crop images captured by drones. However, metaheuristic optimization is …
identify weeds in crop images captured by drones. However, metaheuristic optimization is …
[HTML][HTML] Greenhouse gas emissions trends and mitigation measures in australian agriculture sector—a review
H Panchasara, NH Samrat, N Islam - Agriculture, 2021 - mdpi.com
Agriculture is an important source of greenhouse gas emissions. It is one of the economic
sectors that impacts both directly and indirectly towards climate change which contributes to …
sectors that impacts both directly and indirectly towards climate change which contributes to …
[HTML][HTML] Recent advancements and challenges of AIoT application in smart agriculture: a review
As the most popular technologies of the 21st century, artificial intelligence (AI) and the
internet of things (IoT) are the most effective paradigms that have played a vital role in …
internet of things (IoT) are the most effective paradigms that have played a vital role in …
[HTML][HTML] A cloud enabled crop recommendation platform for machine learning-driven precision farming
Modern agriculture incorporated a portfolio of technologies to meet the current demand for
agricultural food production, in terms of both quality and quantity. In this technology-driven …
agricultural food production, in terms of both quality and quantity. In this technology-driven …