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Synergistic use of handcrafted and deep learning features for tomato leaf disease classification

Research article (Scientific Reports, 2024) · cited 13× · AI/ML
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Synergistic use of handcrafted and deep learning features for tomato leaf disease classification

Summary

Synergistic use of handcrafted and deep learning features for tomato leaf disease classification is a scholarly article[1].

Key Facts

  • Synergistic use of handcrafted and deep learning features for tomato leaf disease classification's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Synergistic use of handcrafted and deep learning features for tomato leaf disease classification. Retrieved May 24, 2026, from https://4ort.xyz/entity/synergistic-use-of-handcrafted-and-deep-learning-features-for-tomato-leaf-disease-classification
MLA “Synergistic use of handcrafted and deep learning features for tomato leaf disease classification.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/synergistic-use-of-handcrafted-and-deep-learning-features-for-tomato-leaf-disease-classification.
BibTeX @misc{4ortxyz_synergistic-use-of-handcrafted-and-deep-learning-features-for-tomato-leaf-disease-classification_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Synergistic use of handcrafted and deep learning features for tomato leaf disease classification}}, year = {2026}, url = {https://4ort.xyz/entity/synergistic-use-of-handcrafted-and-deep-learning-features-for-tomato-leaf-disease-classification}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Synergistic use of handcrafted and deep learning features for tomato leaf disease classification — https://4ort.xyz/entity/synergistic-use-of-handcrafted-and-deep-learning-features-for-tomato-leaf-disease-classification (retrieved 2026-05-24)

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