دورية أكاديمية

Deep learning-assisted comparative analysis of animal trajectories with DeepHL

التفاصيل البيبلوغرافية
العنوان: Deep learning-assisted comparative analysis of animal trajectories with DeepHL
المؤلفون: 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
المصدر: Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
بيانات النشر: Nature Portfolio, 2020.
سنة النشر: 2020
المجموعة: LCC:Science
مصطلحات موضوعية: Science
الوصف: Comparative analysis of animal behaviour using locomotion data such as GPS data is difficult because the large amount of data makes it difficult to contrast group differences. Here the authors apply deep learning to detect and highlight trajectories characteristic of a group across scales of millimetres to hundreds of kilometres.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2041-1723
العلاقة: https://doaj.org/toc/2041-1723Test
DOI: 10.1038/s41467-020-19105-0
الوصول الحر: https://doaj.org/article/a6fc41cd07034a559224fe04d3413b43Test
رقم الانضمام: edsdoj.6fc41cd07034a559224fe04d3413b43
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20411723
DOI:10.1038/s41467-020-19105-0