Zobrazeno 1 - 10
of 107
pro vyhledávání: '"crop detection"'
Autor:
Arantza Bereciartua-Pérez, María Monzón, Daniel Múgica, Greta De Both, Jeroen Baert, Brittany Hedges, Nicole Fox, Jone Echazarra, Ramón Navarra-Mestre
Publikováno v:
Artificial Intelligence in Agriculture, Vol 13, Iss , Pp 18-31 (2024)
Estimation of damage in plants is a key issue for crop protection. Currently, experts in the field manually assess the plots. This is a time-consuming task that can be automated thanks to the latest technology in computer vision (CV). The use of imag
Externí odkaz:
https://doaj.org/article/4ebf665d342643e98dcdff5727dbd928
Autor:
Daniele Sasso, Francesco Lodato, Anna Sabatini, Giorgio Pennazza, Luca Vollero, Marco Santonico, Mario Merone
Publikováno v:
Artificial Intelligence in Agriculture, Vol 12, Iss , Pp 97-108 (2024)
Mapping hazelnut orchards can facilitate land planning and utilization policies, supporting the development of cooperative precision farming systems. The present work faces the detection of hazelnut crops using optical and radar remote sensing data.
Externí odkaz:
https://doaj.org/article/0be6c6778e7541a5b3e7d31acba9aea2
Publikováno v:
Data in Brief, Vol 55, Iss , Pp 110649- (2024)
Technology infusion in agriculture has been progressing steadily, touching upon various spheres of agriculture such as crop identification, soil classification, yield prediction, disease detection, and weed-crop discrimination. On-demand crop type de
Externí odkaz:
https://doaj.org/article/ef2fcf25fb3e4b629049f264757ade10
Autor:
Mahmood Ashraf, Lihui Chen, Nisreen Innab, Muhammad Umer, Jamel Baili, Tai-Hoon Kim, Imran Ashraf
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12649-12665 (2024)
Recent developments and the widespread adoption of remote sensing data (RSD) gave rise to various hyperspectral imaging (HSI) applications. With its detailed spectral information, HSI has been adopted for use in various agriculture-related applicatio
Externí odkaz:
https://doaj.org/article/c4ef72470ae5457aace7a128dc854d32
Autor:
Francesco Lodato, Giorgio Pennazza, Marco Santonico, Luca Vollero, Simone Grasso, Maurizio Pollino
Publikováno v:
Remote Sensing, Vol 16, Iss 7, p 1227 (2024)
The production of “Nocciola Romana” hazelnuts in the province of Viterbo, Italy, has evolved into a highly efficient and profitable agro-industrial system. Our approach is based on a hierarchical framework utilizing aggregated data from multiple
Externí odkaz:
https://doaj.org/article/e2fa3085290c4fe2b4ad51d2a1e7e7b2
Autor:
Thanaporn Singhpoo, Khwantri Saengprachatanarug, Seree Wongpichet, Jetsada Posom, Kanda Runapongsa Saikaew
Publikováno v:
Journal of Agricultural Engineering, Vol 54, Iss 2 (2023)
The quality of fresh cassava roots can be increased through the use of precision equipment. As a first step towards developing an automatic cassava root cutting system, this study demonstrates the use of a computer vision system with deep learning fo
Externí odkaz:
https://doaj.org/article/9727524864fe4e4d8001e64cacc41f44
Akademický článek
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Akademický článek
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Akademický článek
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Autor:
Teodora Selea
Publikováno v:
Remote Sensing, Vol 15, Iss 12, p 2980 (2023)
With the increasing volume of collected Earth observation (EO) data, artificial intelligence (AI) methods have become state-of-the-art in processing and analyzing them. However, there is still a lack of high-quality, large-scale EO datasets for train
Externí odkaz:
https://doaj.org/article/26952d32de224b5186bf76b42f2d084f