# A Public Image Database for Benchmark of Plant Seedling Classification Algorithms

arXiv: https://arxiv.org/abs/1711.05458 · HTML: https://mlsanity.com/paper/1711.05458/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Nov 2017.

## Built on by (most cited first, 20 of 20)

- [A Survey of Deep Learning Techniques for Weed Detection from Images](https://mlsanity.com/paper/2103.01415/) (2021)
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- [A Novel lightweight Convolutional Neural Network, ExquisiteNetV2](https://mlsanity.com/paper/2105.09008/) (2021)
- [CWD30: A Comprehensive and Holistic Dataset for Crop Weed Recognition in Precision Agriculture](https://mlsanity.com/paper/2305.10084/) (2023)
- [Global Wheat Challenge 2020: Analysis of the competition design and winning models](https://mlsanity.com/paper/2105.06182/) (2021)
- [Semi-Supervised Learning for Image Classification using Compact Networks in the BioMedical Context](https://mlsanity.com/paper/2205.09678/) (2022)
- [Multispectral Fine-Grained Classification of Blackgrass in Wheat and Barley Crops](https://mlsanity.com/paper/2405.02218/) (2024)
- [AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock](https://mlsanity.com/paper/2507.22101/) (2025)

## Abstract (arXiv)

A database of images of approximately 960 unique plants belonging to 12 species at several growth stages is made publicly available. It comprises annotated RGB images with a physical resolution of roughly 10 pixels per mm. To standardise the evaluation of classification results obtained with the database, a benchmark based on f1 scores is proposed. The dataset is available at https://vision.eng.au.dk/plant-seedlings-dataset