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Related Experiment Video

Updated: Jan 9, 2026

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
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Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

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Image-based cotton leaf disease diagnosis using YOLO and faster R-CNN techniques

S Chinnadurai1, S Selvakumar2

  • 1Department of Computer Science and Engineering, Dhanalakshmi Srinivasan University, Tiruchirappalli, Tamil Nadu, India.

Scientific Reports
|December 1, 2025
PubMed
Summary

No abstract available in PubMed .

Keywords:
Cotton leaf diseaseDeep learningFaster R-CNNObject detectionSmart agricultureYOLOv5

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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