Efficient pollen grain classification using pre-trained Convolutional Neural Networks: a comprehensive study

Efficient pollen grain classification using pre-trained Convolutional Neural Networks: a comprehensive study

Abstract Pollen identification is necessary for several subfields of geology, ecology, and evolutionary biology. However, the existing methods for pollen identification are laborious, time-consuming, and require highly skilled scientists. Therefore, there is a pressing need for an automated and accu...

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Bibliographic Details
Main Authors: Masoud A. Rostami, Behnaz Balmaki, Lee A. Dyer, Julie M. Allen, Mohamed F. Sallam, Fabrizio Frontalini
Format: Article
Language:English
Published: SpringerOpen 2023-10-01
Series:Journal of Big Data
Subjects:
Pollen identification
Deep learning
Transfer learning
Convolutional Neural Networks
Great basin
Online Access:https://doi.org/10.1186/s40537-023-00815-3

Internet

https://doi.org/10.1186/s40537-023-00815-3

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