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ナガヤ ナオヒサ
NAGAYA NAOHISA
永谷 直久 所属 京都産業大学 情報理工学部 情報理工学科 職種 准教授 |
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| 言語種別 | 英語 |
| 発行・発表の年月 | 2020/10 |
| 形態種別 | 研究論文 |
| 査読 | 査読あり |
| 標題 | Deep learning-assisted comparative analysis of animal trajectories with DeepHL. |
| 執筆形態 | その他 |
| 掲載誌名 | Nature communications |
| 掲載区分 | 国外 |
| 巻・号・頁 | 11(1),pp.5316-5316 |
| 著者・共著者 | Takuya Maekawa,Kazuya Ohara,Yizhe Zhang,Matasaburo Fukutomi,Sakiko Matsumoto,Kentarou Matsumura,Hisashi Shidara,Shuhei J Yamazaki,Ryusuke Fujisawa,Kaoru Ide,Naohisa Nagaya,Koji Yamazaki,Shinsuke Koike,Takahisa Miyatake,Koutarou D Kimura,Hiroto Ogawa,Susumu Takahashi,Ken Yoda |
| 概要 | A comparative analysis of animal behavior (e.g., male vs. female groups) has been widely used to elucidate behavior specific to one group since pre-Darwinian times. However, big data generated by new sensing technologies, e.g., GPS, makes it difficult for them to contrast group differences manually. This study introduces DeepHL, a deep learning-assisted platform for the comparative analysis of animal movement data, i.e., trajectories. This software uses a deep neural network based on an attention mechanism to automatically detect segments in trajectories that are characteristic of one group. It then highlights these segments in visualized trajectories, enabling biologists to focus on these segments, and helps them reveal the underlying meaning of the highlighted segments to facilitate formulating new hypotheses. We tested the platform on a variety of trajectories of worms, insects, mice, bears, and seabirds across a scale from millimeters to hundreds of kilometers, revealing new movement features of these animals. |
| DOI | 10.1038/s41467-020-19105-0 |
| PMID | 33082335 |