A systematic literature review on crop yield prediction with deep learning and remote sensing
Deep learning has emerged as a potential tool for crop yield prediction, allowing the model
to automatically extract features and learn from the datasets. Meanwhile, smart farming …
to automatically extract features and learn from the datasets. Meanwhile, smart farming …
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 …
Forecasting of crop yield using remote sensing data, agrarian factors and machine learning approaches
The art of predicting crop production is done before the crop is harvested. Crop output
forecasts will help people make timely judgments concerning food policy, prices in markets …
forecasts will help people make timely judgments concerning food policy, prices in markets …
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 …
Greenhouse gas emissions trends and mitigation measures in Australian agriculture sector—A review
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 …
Artificial intelligence framework for modeling and predicting crop yield to enhance food security in Saudi Arabia
Predicting crop yields is a critical issue in agricultural production optimization and
intensification research. Accurate foresights of natural circumstances a year in advance can …
intensification research. Accurate foresights of natural circumstances a year in advance can …
Deep convolutional neural networks for weeds and crops discrimination from UAS imagery
L Hashemi-Beni, A Gebrehiwot… - Frontiers in Remote …, 2022 - frontiersin.org
Weeds are among the significant factors that could harm crop yield by invading crops and
smother pastures, and significantly decrease the quality of the harvested crops. Herbicides …
smother pastures, and significantly decrease the quality of the harvested crops. Herbicides …
Smart farming through responsible leadership in Bangladesh: possibilities, opportunities, and beyond
Smart farming has the potential to overcome the challenge of 2050 to feed 10 billion people.
Both artificial intelligence (AI) and the internet of things (IoT) have become critical …
Both artificial intelligence (AI) and the internet of things (IoT) have become critical …
Autonomous detection of mouse-ear hawkweed using drones, multispectral imagery and supervised machine learning
Hawkweeds (Pilosella spp.) have become a severe and rapidly invading weed in pasture
lands and forest meadows of New Zealand. Detection of hawkweed infestations is essential …
lands and forest meadows of New Zealand. Detection of hawkweed infestations is essential …
[HTML][HTML] A Comprehensive Survey of Drones for Turfgrass Monitoring
Drones are being used for agriculture monitoring in many different crops. Nevertheless, the
use of drones for green areas' evaluation is limited, and information is scattered. In this …
use of drones for green areas' evaluation is limited, and information is scattered. In this …