A New Task: Deriving Semantic Class Targets for the Physical Sciences
Instrumentation and Methods for Astrophysics
2022-10-28 v2 Computation and Language
Abstract
We define deriving semantic class targets as a novel multi-modal task. By doing so, we aim to improve classification schemes in the physical sciences which can be severely abstracted and obfuscating. We address this task for upcoming radio astronomy surveys and present the derived semantic radio galaxy morphology class targets.
Cite
@article{arxiv.2210.14760,
title = {A New Task: Deriving Semantic Class Targets for the Physical Sciences},
author = {Micah Bowles and Hongming Tang and Eleni Vardoulaki and Emma L. Alexander and Yan Luo and Lawrence Rudnick and Mike Walmsley and Fiona Porter and Anna M. M. Scaife and Inigo Val Slijepcevic and Gary Segal},
journal= {arXiv preprint arXiv:2210.14760},
year = {2022}
}
Comments
6 pages, 1 figure, Accepted at Fifth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2022), Neural Information Processing Systems 2022