Improved Prediction of Aquatic Beetle Diversity in a Stagnant Pool by a One-Dimensional Convolutional Neural Network Using Variational Autoencoder Generative Adversarial Network-Generated Data
Building a reasonable model for predicting biodiversity using limited data is challenging. Expanding limited experimental data using a variational autoencoder generative adversarial network (VAEGAN) to improve biodiversity predictions for a region is a new strategy. Aquatic beetle diversity in a lar...
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| Published in: | Applied sciences Vol. 13; no. 15; p. 8841 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Basel
MDPI AG
01.08.2023
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| Subjects: | |
| ISSN: | 2076-3417, 2076-3417 |
| Online Access: | Get full text |
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