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Pregled bibliografske jedinice broj: 1104206

From machine learning to deep learning in agriculture-the quantitative review of trends


Đokić, Kristian; Blašković, Lucija; Mandušić, Dubravka
From machine learning to deep learning in agriculture-the quantitative review of trends // IOP Conference Series: Earth and Environmental Science
Taškent, Uzbekistan: IOP Publishing Ltd, 2020. 012138, 15 doi:10.1088/1755-1315/614/1/012138 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1104206 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
From machine learning to deep learning in agriculture-the quantitative review of trends

Autori
Đokić, Kristian ; Blašković, Lucija ; Mandušić, Dubravka

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
IOP Conference Series: Earth and Environmental Science / - : IOP Publishing Ltd, 2020

Skup
1st International Conference on Energetics, Civil and Agricultural Engineering

Mjesto i datum
Taškent, Uzbekistan, 14-16.10.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Agricultural engineering ; Agricultural robots ; Agriculture ; Deep learning ; Learning systems

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Poljoprivreda (agronomija), Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Agronomski fakultet, Zagreb,
Veleučilište u Požegi

Citiraj ovu publikaciju

Đokić, Kristian; Blašković, Lucija; Mandušić, Dubravka
From machine learning to deep learning in agriculture-the quantitative review of trends // IOP Conference Series: Earth and Environmental Science
Taškent, Uzbekistan: IOP Publishing Ltd, 2020. 012138, 15 doi:10.1088/1755-1315/614/1/012138 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Đokić, K., Blašković, L. & Mandušić, D. (2020) From machine learning to deep learning in agriculture-the quantitative review of trends. U: IOP Conference Series: Earth and Environmental Science doi:10.1088/1755-1315/614/1/012138.
@article{article, year = {2020}, pages = {15}, DOI = {10.1088/1755-1315/614/1/012138}, chapter = {012138}, keywords = {Agricultural engineering, Agricultural robots, Agriculture, Deep learning, Learning systems}, doi = {10.1088/1755-1315/614/1/012138}, title = {From machine learning to deep learning in agriculture-the quantitative review of trends}, keyword = {Agricultural engineering, Agricultural robots, Agriculture, Deep learning, Learning systems}, publisher = {IOP Publishing Ltd}, publisherplace = {Ta\v{s}kent, Uzbekistan}, chapternumber = {012138} }
@article{article, year = {2020}, pages = {15}, DOI = {10.1088/1755-1315/614/1/012138}, chapter = {012138}, keywords = {Agricultural engineering, Agricultural robots, Agriculture, Deep learning, Learning systems}, doi = {10.1088/1755-1315/614/1/012138}, title = {From machine learning to deep learning in agriculture-the quantitative review of trends}, keyword = {Agricultural engineering, Agricultural robots, Agriculture, Deep learning, Learning systems}, publisher = {IOP Publishing Ltd}, publisherplace = {Ta\v{s}kent, Uzbekistan}, chapternumber = {012138} }

Časopis indeksira:


  • Scopus


Citati





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