ISO-690 (author-date, English)

SHI, Yong, XU, Ruijie und QI, Zhiquan, 2025. MSNet: A Novel Deep Learning Framework for Efficient Missing Seedling Detection in Maize Fields. Applied Artificial Intelligence. 1 Dezember 2025. Vol. 39, no. 1, p. 1-25. DOI 10.1080/08839514.2025.2469372.

Elsevier - Harvard (with titles)

Shi, Y., Xu, R., Qi, Z., 2025. MSNet: A Novel Deep Learning Framework for Efficient Missing Seedling Detection in Maize Fields. Applied Artificial Intelligence 39, 1-25. https://doi.org/10.1080/08839514.2025.2469372

American Psychological Association 7th edition

Shi, Y., Xu, R., & Qi, Z. (2025). MSNet: A Novel Deep Learning Framework for Efficient Missing Seedling Detection in Maize Fields. Applied Artificial Intelligence, 39(1), 1-25. https://doi.org/10.1080/08839514.2025.2469372

Springer - Basic (author-date)

Shi Y, Xu R, Qi Z (2025) MSNet: A Novel Deep Learning Framework for Efficient Missing Seedling Detection in Maize Fields.. Applied Artificial Intelligence 39:1-25. https://doi.org/10.1080/08839514.2025.2469372

Juristische Zitierweise (Stüber) (Deutsch)

Shi, Yong/ Xu, Ruijie/ Qi, Zhiquan, MSNet: A Novel Deep Learning Framework for Efficient Missing Seedling Detection in Maize Fields., Applied Artificial Intelligence 2025, 1-25.

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