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A Reproducible Deep Learning Framework for Field-Deployable Classification of Sugarcane Pest Damage Using Ensemble CNNs

Crossref DOI link: https://doi.org/10.1007/s12355-025-01714-y

Published Online: 2026-01-13

Published Print: 2026-04

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Singh, Sugam https://orcid.org/0009-0008-3898-2675
Raj, Chandramani https://orcid.org/0000-0003-1620-297X
Modi, Rajesh U. https://orcid.org/0000-0002-6370-7199
Singh, Shweta https://orcid.org/0000-0002-9433-0742
Baitha, Arun https://orcid.org/0000-0003-1220-0010
Srinivas, K. https://orcid.org/0000-0002-3806-2325
Blessy, V. A. https://orcid.org/0000-0003-0037-1613
Hasan, S. S. https://orcid.org/0000-0003-0436-244X
Viswanathan, R. https://orcid.org/0000-0002-3969-6397
Funding

Funding for this research was provided by:

Indian Institute of Sugarcane Research (M15.10)
License Information

Text and Data Mining valid from 2026-01-13

Version of Record valid from 2026-01-13
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Article History

Received: 5 November 2025

Accepted: 19 December 2025

First Online: 13 January 2026

Declarations

:

: All authors declare no competing interests.

: Not applicable.

: Not applicable.