Zobrazeno 1 - 10
of 77
pro vyhledávání: '"plantvillage"'
Autor:
Ettien A. Adjéi, Kassoum Traoré, Eveline Marie F. W. Sawadogo/Compaoré, William J-L. Amoakon, Nazaire K. Kouassi, Modeste K. Kouassi, Justin S. Pita
Publikováno v:
Frontiers in Agronomy, Vol 6 (2024)
In Côte d’Ivoire, cassava is the source of calories for about 26 million people and generates significant income for stakeholders in the value chain. However, its production is threatened by Cassava Mosaic Disease (CMD), which causes yield losses
Externí odkaz:
https://doaj.org/article/8a58d79c8a464c149c4d660e7a5a30f2
Autor:
Dèwanou Kant David Ahoya, Eveline Marie Fulbert Windinmi Sawadogo-Compaore, Jacob Afouda Yabi, Martine Zandjanakou-Tachin, Jerome Anani Houngue, Serge Sètondji Houedjissin, Justin Simon Pita, Corneille Ahanhanzo
Publikováno v:
Agriculture, Vol 14, Iss 11, p 2001 (2024)
Cassava production in Africa is constrained by number of biotic factors, including cassava mosaic disease (CMD). In response to this challenge, the PlantVillage Nuru application, which employs artificial intelligence for CMD diagnosis, provides farme
Externí odkaz:
https://doaj.org/article/8cf990a726d141a5a5887763787747c2
Autor:
Cemal İhsan Sofuoğlu, Derya Bırant
Publikováno v:
Journal of Agricultural Sciences, Vol 30, Iss 1, Pp 153-165 (2024)
In agriculture, plant disease detection and cures for those diseases are crucial for high crop production and yield sustainably. Improvements in the automated disease detection and analysis areas may provide important benefits for early action that w
Externí odkaz:
https://doaj.org/article/136ce122e37143b898bb9fd2e3e3504d
Publikováno v:
Big Data and Cognitive Computing, Vol 8, Iss 6, p 52 (2024)
Due to the projected increase in food production by 70% in 2050, crops should be additionally protected from diseases and pests to ensure a sufficient food supply. Transfer deep learning approaches provide a more efficient solution than traditional m
Externí odkaz:
https://doaj.org/article/33cc45a698e7441fa2ebbac092d2c68f
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
In this paper, we address the question of achieving high accuracy in deep learning models for agricultural applications through edge computing devices while considering the associated resource constraints. Traditional and state-of-the-art models have
Externí odkaz:
https://doaj.org/article/12c38a7dc40d47c38a1fe57ab640f81e
Akademický článek
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Akademický článek
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Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
In the agricultural sector, identifying plant diseases at their earliest possible stage of infestation still remains a huge challenge with respect to the maximization of crop production and farmers’ income. In recent years, advanced computer vision
Externí odkaz:
https://doaj.org/article/ebcdaee64f4c4dbc805851e42d414536
Publikováno v:
Big Data Analytics and Intelligence: A Perspective for Health Care
Autor:
Naveen N. Malvade, Rajesh Yakkundimath, Girish Saunshi, Mahantesh C. Elemmi, Parashuram Baraki
Publikováno v:
Artificial Intelligence in Agriculture, Vol 6, Iss , Pp 167-175 (2022)
The agriculture sector is no exception to the widespread usage of deep learning tools and techniques. In this paper, an automated detection method on the basis of pre-trained Convolutional Neural Network (CNN) models is proposed to identify and class
Externí odkaz:
https://doaj.org/article/2f32afc45f86476e91d6bca4f6ea2f8a