What question did this study set out to answer?

This research aims to create an automated deep learning model for recognizing landscape imagery in Zhuzhici, a form of classical Chinese poetry.

July 27, 2026Humanities and Social Sciences CommunicationsOpen Access

Innovative pathways for contemporary expression of landscape imagery in classical Chinese poetry: a deep learning-based automatic recognition model for Zhuzhici

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This research aims to create an automated deep learning model for recognizing landscape imagery in Zhuzhici, a form of classical Chinese poetry.
Developed the DA-SikuRoBERTa-BiLSTM-CRF recognition model tailored to classical Chinese poetry.
Evaluated model performance based on precision, recall, and F1 score metrics.
Explored application pathways for historical landscape inventory and knowledge base construction.
Achieved a precision of 87.87%, recall of 83.05%, and F1 score of 85.39%.
Significantly improved recognition accuracy for landscape imagery, including emotionally embedded elements.
Identified potential for the model's application in digital landscape resource mining and spatial planning.

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Implication

Randomized trial develops an automated model for landscape imagery recognition in classical Chinese poetry, suggesting new applications for cultural resources.

Cite This Study

Gao et al. (2026) studied this question.

synapsesocial.com/papers/6a67007840bca442e0d4a272 https://doi.org/10.1057/s41599-026-08423-1

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Implication

Randomized trial develops an automated model for landscape imagery recognition in classical Chinese poetry, suggesting new applications for cultural resources.

Innovative pathways for contemporary expression of landscape imagery in classical Chinese poetry: a deep learning-based automatic recognition model for Zhuzhici

Key Points

Discussion

Implication

Cite This Study

Innovative pathways for contemporary expression of landscape imagery in classical Chinese poetry: a deep learning-based automatic recognition model for Zhuzhici

Key Points

Discussion

Implication

Cite This Study

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