Animal classification considering infrared few-shot open-set recognition

This paper introduced the novel Infrared Few-shot Open-set Recognition (IFOR) framework for effective nighttime wildlife surveillance using limited infrared images. We focused on the effectiveness of three critical methods: small-scale datasets, domain shift, and open-set recognition for addressing...

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Библиографические подробности

Главные авторы:	Koki Kishi, Ranmaru Ito, Sulfayanti F. Situju, Hironori Takimoto, Akihiro Kanagawa
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Taylor & Francis Group 2025-12-01
Серии:	Cogent Engineering
Предметы:	Infrared few-shot open-set recognition few-shot learning meta learning vision transformer infrared image animal classification in camera traps
Online-ссылка:	https://www.tandfonline.com/doi/10.1080/23311916.2025.2560976
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