DiverScan: attention-guided exploratory analysis of animal behaviour across diverse comparative experiments
Momoe Sukegawa, Hirotsugu Azechi, Tatsumi Butsugan, Nadja Freund, Shiomi Hakataya, Tomohiro Iwata, Noriko Katsu, Koutarou D. Kimura, Hiroki Koda, Akiko Koto, Yuya Makiguchi, Hiroshi Matsui, Koji Miyoshi, Annakarina Mundorf, Hiraku Nishimori, , Takuya Maekawa
DiverScan is a deep-learning framework that uses attention mechanisms to analyze animal behavior data, identifying condition-specific features across diverse experiments.
bioRxiv · Oct 8, 2026 · PreprintAnimal Behavior & Cognition