activity
20192022
most citedStar Cluster Classification in the PHANGS-HST Survey: Comparison between Human and Machine Learning Approaches

50 citations · 123 across the 4 of their papers we have counts for

collaborators

5 papers

astro-ph.GA202240 cited

H Morphologies of Star Clusters in 16 LEGUS Galaxies: Constraints on HII region evolution timescales

Stephen Hannon, Janice C. Lee, Bradley C. Whitmore +14

The analysis of star cluster ages in tandem with the morphology of their HII regions can provide insight into the processes that clear a cluster's natal gas, as well as the accurac…

astro-ph.GA202116 cited

Synthetic photometry of OB star clusters with stochastically sampled IMFs: analysis of models and HST observations

Rogelio Orozco-Duarte, Aida Wofford, Alba Vidal-García +13

We present a pilot library of synthetic NUV, U, B, V, and I photometry of star clusters with stochastically sampled IMFs and ionized gas for initial masses, , , and…

astro-ph.GA202150 cited

Star Cluster Classification in the PHANGS-HST Survey: Comparison between Human and Machine Learning Approaches

Bradley C. Whitmore, Janice C. Lee, Rupali Chandar +21

When completed, the PHANGS-HST project will provide a census of roughly 50,000 compact star clusters and associations, as well as human morphological classifications for roughly 20…

astro-ph.SR202017 cited

Candidate LBV stars in galaxy NGC 7793 found via HST photometry + MUSE spectroscopy

Aida Wofford, Vanesa Ramirez, Janice C. Lee +21

Only about 19 Galactic and 25 extra-galactic bona-fide Luminous Blue Variables (LBVs) are known to date. This incomplete census prevents our understanding of this crucial phase of…

astro-ph.GA2019

Deep Transfer Learning for Star Cluster Classification: I. Application to the PHANGS-HST Survey

Wei Wei, E. A. Huerta, Bradley C. Whitmore +13

We present the results of a proof-of-concept experiment which demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters…