High-Throughput Spike Detection in Greenhouse Cultivated Grain Crops with Attention Mechanisms-Based Deep Learning Models Article Swipe

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Sajid Ullah , Klará Panzarová , Martin Trtílek , Matej Lexa , Vojtěch Máčala , Kerstin Neumann , Thomas Altmann , Jan Hejátko , Markéta Pernisová , Evgeny Gladilin ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.34133/plantphenomics.0155

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Spike (software development) Throughput Greenhouse Agronomy Biology Computer science Software engineering Wireless Telecommunications

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Type: article
Language: en
Landing Page: https://doi.org/10.34133/plantphenomics.0155
OA Status: gold
Cited By: 6
References: 18
Related Works: 10
OpenAlex ID: https://openalex.org/W4391755121

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OpenAlex ID: https://openalex.org/W4391755121

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DOI: https://doi.org/10.34133/plantphenomics.0155

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Title: High-Throughput Spike Detection in Greenhouse Cultivated Grain Crops with Attention Mechanisms-Based Deep Learning Models

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Type: article

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Language: en

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Publication year: 2024

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Publication date: 2024-01-01

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Authors: Sajid Ullah, Klará Panzarová, Martin Trtílek, Matej Lexa, Vojtěch Máčala, Kerstin Neumann, Thomas Altmann, Jan Hejátko, Markéta Pernisová, Evgeny Gladilin

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Landing page: https://doi.org/10.34133/plantphenomics.0155

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OA status: gold

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OA URL: https://doi.org/10.34133/plantphenomics.0155

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Concepts: Spike (software development), Throughput, Greenhouse, Agronomy, Biology, Computer science, Software engineering, Wireless, Telecommunications

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Cited by: 6

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Citations by year (recent): 2025: 4, 2024: 2

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