ShuffleNetV2 achieves 99.29% accuracy and 99.35% F1-score in classifying ten Vietnamese timber species from images, outperforming heavier models in speed-accuracy trade-off.
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Deep Learning for Automated Identification of Vietnamese Timber Species: A Tool for Ecological Monitoring and Conservation
ShuffleNetV2 achieves 99.29% accuracy and 99.35% F1-score in classifying ten Vietnamese timber species from images, outperforming heavier models in speed-accuracy trade-off.