학술논문

MARS: the First Romanian Pollen Dataset using a Rapid-E Particle Analyzer
Document Type
Conference
Source
2021 International Conference on Speech Technology and Human-Computer Dialogue (SpeD) Speech Technology and Human-Computer Dialogue (SpeD), 2021 International Conference on. :145-150 Oct, 2021
Subject
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Machine learning algorithms
Databases
Atmospheric measurements
Training data
Machine learning
Particle measurements
Convolutional neural networks
Rapid-E
pollen data-set
pollen classification
Language
Abstract
Pollen allergies are a growing concern for human health. This is why automated pollen monitoring is becoming an important area of research. Machine learning approaches show great promise for tackling this issue but these algorithms need large training data sets to perform well. This study introduces a new pollen data set, obtained using a Rapid-E particle analyzer, that is representative for the flora of Romania. Pollen, from thirteen species present in Romania, was used in developing this database with over 100 thousand samples measured. Our study shows performance similar to or above that of humans in the task of pollen classification on the newly introduced data set using a convolutional neural network.