From machine learning to deep learning in agriculture-the quantitative review of trends (CROSBI ID 698729)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Đokić, Kristian ; Blašković, Lucija ; Mandušić, Dubravka
engleski
From machine learning to deep learning in agriculture-the quantitative review of trends
In the last two decades, we have witnessed the intensive development of artificial intelligence in the field of agriculture. In this period, the transition from the application of simpler machine learning algorithms to the application of deep learning algorithms can be observed. This paper provides a quantitative overview of papers published in the past two decades, thematically related to machine learning, neural networks, and deep learning. Also, a review of the contribution of individual countries was given. The second part of the paper analyses trends in the first half of the current year, with an emphasis on areas of application, selected deep learning methods, input data, crop mentioned in the paper and applied frameworks. Scopus and Web of Science citation databases were used.
Agricultural engineering ; Agricultural robots ; Agriculture ; Deep learning ; Learning systems
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Podaci o prilogu
012138
2020.
objavljeno
10.1088/1755-1315/614/1/012138
Podaci o matičnoj publikaciji
IOP Conference Series: Earth and Environmental Science
IOP Publishing
1755-1307
1755-1315
Podaci o skupu
1st International Conference on Energetics, Civil and Agricultural Engineering 2020 (ICECAE 2020)
predavanje
14.10.2020-16.10.2020
Taškent, Uzbekistan
Povezanost rada
Informacijske i komunikacijske znanosti, Poljoprivreda (agronomija)