Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains.
Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains.
复制标题
用于巴西大草原花粉粒分类的特征提取和机器学习。
DOI：
10.1371/journal.pone.0157044
复制
发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Pistori H
中科院分区：
文献类型：
--
作者：
Gonçalves AB;Souza JS;Silva GG;Cereda MP;Pott A;Naka MH;Pistori H
花粉种类和类型的分类是法医孢粉学、考古孢粉学和蜜环菌孢粉学等许多领域的重要任务。本文介绍了第一个注释的图像数据集的巴西萨凡纳花粉类型，可用于训练和测试基于计算机视觉的自动花粉分类器。使用23种花粉类型的805个花粉图像建立了该数据集的第一个基线人类和计算机性能。为了访问计算机性能，已经实现了三个特征提取器和四个机器学习技术的组合，进行了微调和测试。本文还介绍了这些试验的结果。
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.