Pollen Grain Classification Using Some Convolutional Neural Network Architectures

Pollen Grain Classification Using Some Convolutional Neural Network Architectures

The main objective of this work is to use convolutional neural networks (CNN) to improve the performance in previous works on their baseline for pollen grain classification, by improving the performance of the following eight popular architectures: InceptionV3, VGG16, VGG19, ResNet50, NASNet, Xcepti...

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Bibliographic Details
Main Authors: Benjamin Garga, Hamadjam Abboubakar, Rodrigue Saoungoumi Sourpele, David Libouga Li Gwet, Laurent Bitjoka
Format: Article
Language:English
Published: MDPI AG 2024-06-01
Series:Journal of Imaging
Subjects:
pollen grains
classification
performances
CNN
dataset
POLLEN73S
Online Access:https://www.mdpi.com/2313-433X/10/7/158

Internet

https://www.mdpi.com/2313-433X/10/7/158

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