Infected Tomato Leaf - Vein Segmentation

Projects
ML Marathon
MLM24
Image segmentation
Computer vision
Deep learning
U-Net
Agriculture
Image data
UW-Madison
Author

Chris Endemann

Published

September 12, 2024

The Infected Tomato Leaf - Vein Segmentation challenge was featured in the 2024 Machine Learning Marathon (MLM24). This UW-Madison-originated Kaggle competition focuses on segmenting primary and secondary vein structures from tomato leaf images at varying stages of disease progression.

Challenge design

  • Task: Segment leaf vein structures in images of infected tomato leaves, distinguishing between primary and secondary veins across different disease stages.
  • Domain: Agriculture and plant pathology – automated vein segmentation can help researchers study how diseases affect leaf vascular structure.
  • Methods: Image segmentation approaches, commonly using architectures like U-Net.

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