| 研究実績の概要 |
Deep Learning models have achieved high accuracy in the experimental dataset, demonstrating their capability to learn complex patterns and make accurate predictions. However, when applied to the Jomon dataset, the accuracy was lower than the experimental dataset. Nevertheless, experiments revealed that the models were relying on the morphology of the object to make predictions, which indicates that the results are reliable.
Despite the challenges faced, we remain remain optimistic about the potential of deep learning models to aid the classification of potsherds. Our experiments have shown that the models can rely on object morphology to make accurate predictions, indicating their effectiveness in supporting archaeologists in their studies.
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