CISCS: Classification of inter-class similarity based medicinal plant species groups with machine learning.

N Shobha Rani, Bhavya K R, I Jeena Jacob, Pushpa B R, Bipin Nair Bj, Akshatha Prabhu

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Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

N Shobha RaniMURTI Research Centre, Smart Agriculture Lab, Department of Artificial Intelligence and Data Science, GITAM School of Technology, Bengaluru, GITAM (Deemed to be) University, India.

Bhavya K RMURTI Research Centre, Smart Agriculture Lab, Department of Computer Science and Engineering, GITAM School of Technology, Bengaluru, GITAM (Deemed to be) University, India.

I Jeena JacobMURTI Research Centre, Smart Agriculture Lab, Department of Computer Science and Engineering, GITAM School of Technology, Bengaluru, GITAM (Deemed to be) University, India.

Pushpa B RDepartment of Computer Science, School of Computing, Amrita Vishwa Vidyapeetham, Mysuru, India.

Bipin Nair BjDepartment of Computer Science, School of Computing, Amrita Vishwa Vidyapeetham, Mysuru, India.

Akshatha PrabhuDepartment of Computer Science, School of Computing, Amrita Vishwa Vidyapeetham, Mysuru, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The reliable classification of medicinal plant species plays a vital role in ensuring their quality, authenticity, and safe use in healthcare. However, existing methods often face difficulties when species exhibit strong visual similarities or when datasets are imbalanced, which limits their effectiveness in practice. Although deep learning models such as ResNet18 and VGG16 have proven influential in image recognition tasks, our experiments showed that they tended to overfit, with validation losses reaching 42.99 % and test accuracy falling to 73.99 % in certain groups. To overcome these challenges, we introduce a multi-level fusion feature model that combines 3D normalized color histograms, extended uniform Local Binary Patterns (LBP with

Indexed as

Deep learningHigh inter-class similarityIndian plant speciesIntra-class variationMedicinal plant classification

Identifiers

PMID41140625

DOI10.1016/j.mex.2025.103652

PMCPMC12550246

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.