| Autor: |
Jiyun Hong, Jiwon Lee, Somin Lee, Eun Ko, Gyubin Kim, Jungwoon Kang, Mincheol Kim |
| Předmět: |
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| Zdroj: |
Journal of Information & Communication Convergence Engineering; Sep2024, Vol. 22 Issue 3, p221-230, 10p |
| Abstrakt: |
The aim of this study is to investigate the automatic recognition and analysis of Jeju marine-life images using artificial intelligence (AI) technology. The dataset of marine-life images was prepared using tools such as Python, TensorFlow, and Google Colab (Google Colaboratory). We also developed models by training deep learning AI in image recognition to automatically recognize the species found in these images and extract their associated information, such as taxonomy, characteristics, and distribution. This study is innovative in that it uses deep learning technology combined with imagerecognition technology for marine biodiversity research. In addition, these results will lead to the development of the marine-life industry in Jeju by supporting marine environment monitoring and marine resource conservation. Furthermore, this study is anticipated to contribute to academic advancement, specifically in the study of marine species diversity. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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