Výsledky vyhledávání - "Frank Gyan Okyere"

Akademický článek

Hyperspectral Imaging for Phenotyping Plant Drought Stress and Nitrogen Interactions Using Multivariate Modeling and Machine Learning Techniques in Wheat

Autor: Frank Gyan Okyere, Daniel Kingsley Cudjoe, Nicolas Virlet, March Castle, Andrew Bernard Riche, Latifa Greche, Fady Mohareb, Daniel Simms, Manal Mhada, Malcolm John Hawkesford

Publikováno v: Remote Sensing, Vol 16, Iss 18, p 3446 (2024)

Accurate detection of drought stress in plants is essential for water use efficiency and agricultural output. Hyperspectral imaging (HSI) provides a non-invasive method in plant phenotyping, allowing the long-term monitoring of plant health due to se

Externí odkaz: https://doaj.org/article/ce59b9a504b14cdbaa1d7bc9f86708c5

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Akademický článek

Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods

Autor: Frank Gyan Okyere, Daniel Cudjoe, Pouria Sadeghi-Tehran, Nicolas Virlet, Andrew B. Riche, March Castle, Latifa Greche, Daniel Simms, Manal Mhada, Fady Mohareb, Malcolm John Hawkesford

Publikováno v: Frontiers in Plant Science, Vol 14 (2023)

Sustainable fertilizer management in precision agriculture is essential for both economic and environmental reasons. To effectively manage fertilizer input, various methods are employed to monitor and track plant nutrient status. One such method is h

Externí odkaz: https://doaj.org/article/d55c585466ca4f69987ea302a479ebb0

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Akademický článek

Machine Learning Methods for Automatic Segmentation of Images of Field- and Glasshouse-Based Plants for High-Throughput Phenotyping

Autor: Frank Gyan Okyere, Daniel Cudjoe, Pouria Sadeghi-Tehran, Nicolas Virlet, Andrew B. Riche, March Castle, Latifa Greche, Fady Mohareb, Daniel Simms, Manal Mhada, Malcolm John Hawkesford

Publikováno v: Plants, Vol 12, Iss 10, p 2035 (2023)

Image segmentation is a fundamental but critical step for achieving automated high- throughput phenotyping. While conventional segmentation methods perform well in homogenous environments, the performance decreases when used in more complex environme

Externí odkaz: https://doaj.org/article/8978905b5f7f4babbf4cae606176a408

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Akademický článek

Artificial neural networks and multiple linear regression as potential methods for modelling body surface temperature of pig

Autor: Jayanta Kumar Basak, Frank Gyan Okyere, Elanchezhian Arulmozhi, Jihoon Park, Fawad Khan, Hyeon Tae Kim

Publikováno v: Journal of Applied Animal Research, Vol 48, Iss 1, Pp 207-219 (2020)

An experiment was conducted to evaluate modelling relationships between pig’s body surface temperature and ambient environment including inside and outside of pig barn. For this purpose, four different artificial neural network (ANN), including Fee

Externí odkaz: https://doaj.org/article/14aa951e4115446c9dd5755c827d2dce

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Akademický článek

Composting of chicken manure with a mixture of sawdust and wood shavings under forced aeration in a closed reactor system

Autor: Waqas Qasim, Min Ho Lee, Byeong Eun Moon, Frank Gyan Okyere, Fawad Khan, Mohammad Nafees, Hyeon Tae Kim

Publikováno v: International Journal of Recycling of Organic Waste in Agriculture, Vol 7, Iss 3, Pp 261-267 (2018)

Abstract Purpose This study aimed to achieve successful composting and aeration rate and to optimize the carbon:nitrogen (C:N) ratio to provide favourable conditions for the process. In the current experiment, investigation were made on variations in

Externí odkaz: https://doaj.org/article/cff2179f9faf4379bdb9b1a4727e8188

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Akademický článek

A Partially Amended Hybrid Bi-GRU—ARIMA Model (PAHM) for Predicting Solar Irradiance in Short and Very-Short Terms

Autor: Mustafa Jaihuni, Jayanta Kumar Basak, Fawad Khan, Frank Gyan Okyere, Elanchezhian Arulmozhi, Anil Bhujel, Jihoon Park, Lee Deog Hyun, Hyeon Tae Kim

Publikováno v: Energies, Vol 13, Iss 2, p 435 (2020)

Solar renewable energy (SRE) applications are substantial in eradicating the rising global energy shortages and reversing the approaching environmental apocalypse. Hence, effective solar irradiance forecasting models are crucial in utilizing SRE effi

Externí odkaz: https://doaj.org/article/ca24e2a6d2534974a48260bde334e490

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A novel recurrent neural network approach in forecasting short term solar irradiance

Autor: Frank Gyan Okyere, Fawad Khan, Hyeon Tae Kim, Thavisak Sihalath, Deog Hyun Lee, Jihoon Park, Anil Bhujel, Mustafa Jaihuni, Jayanta Kumar Basak

Publikováno v: ISA Transactions. 121:63-74

Forecasting solar irradiance is of utmost importance in supplying renewable energy efficiently and timely. This paper aims to experiment five variants of recurrent neural networks (RNN), and develop effective and reliable 5-minute short term solar ir

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4166aa1d5eb5e198421bd542e31188fc
https://doi.org/10.1016/j.isatra.2021.03.043

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