Computer Vision Challenge for Cucumber Growth Stage Classification
Discord Server Go to CompetitionFood safety and agricultural sustainability benefit from timely management practices that reduce losses and optimize inputs.
Participants must predict the phenological stage of cucumber crops from images under real-world conditions.
| Class | Description |
|---|---|
| plantula | Seedling |
| early_vegetative | Early vegetative |
| vegetative_growth | Growth |
| flowering | Flowering |
| fruit_setting | Fruit setting |
File structure:
submission.zip └── submission.csv
CSV Example:
image_id,stage_pred img_000001.jpg,plantula
NALEF 2026 will be held in person on August 12, 13, and 14, 2026, at the Almirante Padilla Naval Academy in Cartagena, Colombia, as part of the 20th Colombian Computing Congress (20CCC).
Participants are invited to submit system description papers (5 to 8 pages) in English, addressing one of the following tasks: Task 1: Food Safety or Task 2: GastroCorp NER.
Submissions must be original and unpublished. Accepted papers will be published in the workshop proceedings in the CEUR Workshop Proceedings series (CEUR-WS.org, ISSN 1613-0073).
System description papers must be 5 to 8 pages long, including references and appendices. They must be written in English using the CEURART template, without including author names to enable anonymous review (LaTeX or Overleaf format).
All submissions will undergo peer review by the program committee. Evaluation criteria will include: relevance, technical/scientific quality, clarity, and suitability for the workshop tasks.
Papers must be submitted through the OpenReview platform. Accepted papers will be published in open access under the CC BY 4.0 license.
Submit via OpenReview