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 …
[HTML][HTML] Crop yield prediction using machine learning: A systematic literature review
T Van Klompenburg, A Kassahun, C Catal - Computers and electronics in …, 2020 - Elsevier
Abstract Machine learning is an important decision support tool for crop yield prediction,
including supporting decisions on what crops to grow and what to do during the growing …
including supporting decisions on what crops to grow and what to do during the growing …
Technological revolutions in smart farming: Current trends, challenges & future directions
With increasing population, the demand for agricultural productivity is rising to meet the goal
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …
A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
An early and reliable estimation of crop yield is essential in quantitative and financial
evaluation at the field level for determining strategic plans in agricultural commodities for …
evaluation at the field level for determining strategic plans in agricultural commodities for …
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 …
Corn emergence uniformity estimation and mapping using UAV imagery and deep learning
Abstract Assessment of corn (Zea Mays L.) emergence uniformity is important to evaluate
crop yield potential. Previous studies have shown the potential of unmanned aerial vehicle …
crop yield potential. Previous studies have shown the potential of unmanned aerial vehicle …
Review on crop prediction using deep learning techniques
MK Dharani, R Thamilselvan, P Natesan… - Journal of physics …, 2021 - iopscience.iop.org
Agriculture is the very important sector of each country, where the gross domestic pay relies
on it. The outcome of the agriculture or crop management was completely based on the end …
on it. The outcome of the agriculture or crop management was completely based on the end …
Exploration of machine learning approaches for paddy yield prediction in eastern part of Tamilnadu
V Joshua, SM Priyadharson, R Kannadasan - Agronomy, 2021 - mdpi.com
Agriculture is the principal basis of livelihood that acts as a mainstay of any country. There
are several changes faced by the farmers due to various factors such as water shortage …
are several changes faced by the farmers due to various factors such as water shortage …
Temporal convolutional network based rice crop yield prediction using multispectral satellite data
A Mohan, M Venkatesan, P Prabhavathy… - Infrared Physics & …, 2023 - Elsevier
Early prediction of crop yield has a significant role in ensuring food security. The crop yield
depends on several parameters, such as vegetation parameters, climatic parameters, soil …
depends on several parameters, such as vegetation parameters, climatic parameters, soil …
A systematic review on crop-yield prediction through unmanned aerial vehicles
In recent years, with the increase in big data technologies the Machine learning is an
important decision support tool, smart farming observes the behavior of climate change over …
important decision support tool, smart farming observes the behavior of climate change over …