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·2024
Dataset Generation for Korean Urban Parks Analysis with Large Language Models
H. S. Kim, M.-S. Kang, Hyeyoung Choi, Yun-Gyung Cheong
초록

Understanding how urban parks are utilized and perceived by the public is crucial for effective urban planning and management. This study introduces a novel dataset derived from Instagram, using 42,187 images tagged with #Seoul and #Park hashtags from 2017 to 2023. These images were filtered using InternLM-XComposer2, a Multimodal Large Language Model (MLLM), to confirm they depicted park scenes. GPT-4 then annotated the filtered images, resulting in 29,866 valid image annotations of physical elements, human activities, animals, and emotions. The dataset is publicly available at https://huggingface.co/datasets/RedBall/seoul-urban-park-analysis-by-llm.

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Computer scienceNatural language processing
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article
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- / 0
게재 연도
2024

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