Profile
Contact
Behavior Signal Processing Lab (Takeda & Fujii lab), Graduate School of Informatics, Nagoya University
Room 825, IB North Building, Nagoya University, Furocho 1, Nagoya, 464-8603, JAPAN
email: kaiamino417[at]gmail.com
Education
2024.3 Graduate School of Agriculture and Life Sciences, University of Tokyo (Ph.D.)
2021.3 Graduate School of Agriculture and Life Sciences, University of Tokyo (MS)
2019.3 Faculty of Agriculture, University of Tokyo (BS)
Grants
2024.4~ JSPS Research Fellowship (PD) 3,000,000 JPY
2021.10~2024.3 JST Strategic Basic Research Programs ACT-X 5,000,000 JPY
2021.4月~2024.3 JSPS Research Fellowship (DC1) 2,100,000 JPY
Achievements
Journal paper (peer-reviewed)
Kai Amino*, Tsubasa Hirakawa, Masaya Yago and Takashi Matsuo (2025) Dorsoventral comparison of intraspecific variation in the butterfly wing pattern using a convolutional neural network. Biology Letters, 21, 20240446.
Kai Amino* and Takashi Matsuo (2023) Effects of a past contest outcome on the future winning probability in a hyper-aggressive fruit fly. Ethology, 129, 380-389.
Kai Amino* and Takashi Matsuo (2023) Reproductive advantage of the winners of male-male competition in Drosophila prolongata. Behavioural Processes, 206, 104831.
Kazuyoshi Minekawa, Kai Amino and Takashi Matsuo* (2020) A courtship behavior that makes monandrous females polyandrous. Evolution, 74, 2483–2493.
Kai Amino and Takashi Matsuo* (2020) Intra- versus inter-sexual selection on sexually dimorphic traits in Drosophila prolongata. Zoological Science, 37, 210-216.
Conference paper (peer-reviewed)
Kai Amino and Keisuke Fujii (2024) ButterFlySet: A 2D video dataset for pose estimation of the flying butterflies in the wild. Visual observation and analysis of Vertebrate And Insect Behavior 2024.
Other Publication (not peer-reviewed)
Kai Amino & Takashi Matsuo (2022) Automated Behavior Analysis Using a YOLO-Based Object Detection System. In: Yamamoto D (ed) Behavioral Neurogenetics. Springer, New York, pp 257–275.
Presentations (not peer-reviewed)
Kai Amino, Tsubasa Hirakawa, Masaya Yago & Takashi Matsuo. Quantitative analysis of mimetic traits in butterflies using deep learning: An attempt to imitate predator responses. International Congress of Entomology (ICE2024), Japan, August, 2024, Oral.
Kai Amino, Tsubasa Hirakawa, Masaya Yago & Takashi Matsuo. Quantification of mimicry resemblance in butterflies using feature extractor of deep neural network. Congresses of the European Society for Evolutionary Biology (ESEB), Czech Republic, August, 2022, Poster.