Machine-learning-based high-speed automated analysis of nuclear-emulsion for understanding the spatial distribution of radioactive elements in rocks

Nishikiori Tsukasa

Presentation information

[J] Oral

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI39] Data-driven Earth and planetary science: From numerical modeling to natural data analysis

Thu. May 28, 2026 9:00 AM - 10:30 AM Exhibition Hall Special Setting (7) (Exhibition Hall 7&8, Makuhari Messe)

Chairperson:Ueki Kenta(Japan Agency for Marine-Earth Science and Technology), Itano Keita(Akita University)

9:30 AM - 9:45 AM

[MGI39-03] Machine-learning-based high-speed automated analysis of nuclear-emulsion for understanding the spatial distribution of radioactive elements in rocks

*Nishikiori Tsukasa¹, Tsutomu FUKUDA¹, Sota Niki¹, Yui Kouketsu¹, Shogo Nagahara¹, Soichi Takeshita¹, Naotaka Naganawa¹, Tsuyoshi Kawahara¹, Tomokazu Matsuo¹, Leona Suzui¹, Tsuyoshi Iizuka⁴, Nozomu Takeuchi⁴, Satoru Haraguchi⁴, Kenta Ueki³, Sanshiro Enomoto², Akiko Tanaka⁵, Marin Takano⁶, Akihiro Minamino⁶ (1. Nagoya Univ., 2. Univ. of Washington, 3. JAMSTEC, 4. Tokyo Univ., 5. Tohoku Univ., 6. Yokohama National Univ.)