A Public Image Database for Benchmark of Plant Seedling Classification Algorithms

11/15/2017

∙

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 f_1 scores is proposed. The dataset is available at https://vision.eng.au.dk/plant-seedlings-dataset

READ FULL TEXT

A Public Image Database for Benchmark of Plant Seedling Classification Algorithms

Scalable learning for bridging the species gap in image-based plant phenotyping

Deep Convolutional Neural Network for Plant Seedlings Classification

PlantDet: A benchmark for Plant Detection in the Three-Rivers-Source Region

Presenting an extensive lab- and field-image dataset of crops and weeds for computer vision tasks in agriculture

DAVIS-Ag: A Synthetic Plant Dataset for Developing Domain-Inspired Active Vision in Agricultural Robots

Leaf segmentation through the classification of edges

Multi-resolution Outlier Pooling for Sorghum Classification

A Public Image Database for Benchmark of Plant Seedling Classification Algorithms

Related Research

Scalable learning for bridging the species gap in image-based plant phenotyping

Deep Convolutional Neural Network for Plant Seedlings Classification

PlantDet: A benchmark for Plant Detection in the Three-Rivers-Source Region

Presenting an extensive lab- and field-image dataset of crops and weeds for computer vision tasks in agriculture

DAVIS-Ag: A Synthetic Plant Dataset for Developing Domain-Inspired Active Vision in Agricultural Robots

Leaf segmentation through the classification of edges

Multi-resolution Outlier Pooling for Sorghum Classification