wovepaper — the arXiv observatory

papers

Publications (2)

hep-ex2024

A novel machine learning method to detect double- $I^$ hypernuclear events in nuclear emulsions

Yan He, Vasyl Drozd, Hiroyuki Ekawa +17

A novel method was developed to detect double- $I^$ hypernuclear events in nuclear emulsions using machine learning techniques. The object detection model, the Mask R-CNN, was train…

nucl-ex2025

Binding energy of $_{I^}^{3} H$ and $_{I^}^{4} H$ via image analyses of nuclear emulsions using deep-learning

Ayumi Kasagi, Takehiko R. Saito, Vasyl Drozd +16

Subatomic systems are pivotal for understanding fundamental baryonic interactions, as they provide direct access to quark-level degrees of freedom. In particular, introducing a str…

Publications (2)

A novel machine learning method to detect double-I^ hypernuclear events in nuclear emulsions

Binding energy of I^3​H and I^4​H via image analyses of nuclear emulsions using deep-learning

A novel machine learning method to detect double- $I^$ hypernuclear events in nuclear emulsions

Binding energy of $_{I^}^{3} H$ and $_{I^}^{4} H$ via image analyses of nuclear emulsions using deep-learning