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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] The digitization of agricultural industry–a systematic literature review on agriculture 4.0
Agriculture is considered one of the most important sectors that play a strategic role in
ensuring food security. However, with the increasing world's population, agri-food demands …
ensuring food security. However, with the increasing world's population, agri-food demands …
Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
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 …
Automation in agriculture by machine and deep learning techniques: A review of recent developments
Recently, agriculture has gained much attention regarding automation by artificial
intelligence techniques and robotic systems. Particularly, with the advancements in machine …
intelligence techniques and robotic systems. Particularly, with the advancements in machine …
[HTML][HTML] Review of weed detection methods based on computer vision
Z Wu, Y Chen, B Zhao, X Kang, Y Ding - Sensors, 2021 - mdpi.com
Weeds are one of the most important factors affecting agricultural production. The waste and
pollution of farmland ecological environment caused by full-coverage chemical herbicide …
pollution of farmland ecological environment caused by full-coverage chemical herbicide …
A systematic literature review on machine learning applications for sustainable agriculture supply chain performance
Agriculture plays an important role in sustaining all human activities. Major challenges such
as overpopulation, competition for resources poses a threat to the food security of the planet …
as overpopulation, competition for resources poses a threat to the food security of the planet …
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 …
A review on weed detection using ground-based machine vision and image processing techniques
A Wang, W Zhang, X Wei - Computers and electronics in agriculture, 2019 - Elsevier
Weeds are among the major factors that could harm crop yield. With the advances in
electronic and information technologies, machine vision combined with image processing …
electronic and information technologies, machine vision combined with image processing …
Weed detection in sesame fields using a YOLO model with an enhanced attention mechanism and feature fusion
J Chen, H Wang, H Zhang, T Luo, D Wei, T Long… - … and Electronics in …, 2022 - Elsevier
Weeds have a significant impact on sesame throughout its early stages of development, thus
they must be rigorously controlled. However, the shape of sesame seedlings and weeds are …
they must be rigorously controlled. However, the shape of sesame seedlings and weeds are …