Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains.
Where this comes from
- Record sourced from PubMed, PMID 27276196.
- Also identified by DOI 10.1371/journal.pone.0157044 and PMC identifier 4898734.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
The classification of pollen species and types is an important task in many areas like forensic palynology, archaeological palynology and melissopalynology. This paper presents the first annotated image dataset for the Brazilian Savannah pollen types that can be used to train and test computer vision based automatic pollen classifiers. A first baseline human and computer performance for this dataset has been established using 805 pollen images of 23 pollen types. In order to access the computer performance, a combination of three feature extractors and four machine learning techniques has been implemented, fine tuned and tested. The results of these tests are also presented in this paper.
Medical subject headings
- Grassland
- Machine Learning
- Pollen