16 citations · 39 across the 3 of their papers we have counts for
3 papers
astro-ph.SR2022★ 8 cited
Inferring Line-of-Sight Velocities and Doppler Widths from Stokes Profiles of GST/NIRIS Using Stacked Deep Neural Networks
Haodi Jiang, Qin Li, Yan Xu +5
Obtaining high-quality magnetic and velocity fields through Stokes inversion is crucial in solar physics. In this paper, we present a new deep learning method, named Stacked Deep N…
astro-ph.SR2021★ 16 cited
Tracing Halpha Fibrils through Bayesian Deep Learning
Haodi Jiang, Ju Jing, Jiasheng Wang +5
We present a new deep learning method, dubbed FibrilNet, for tracing chromospheric fibrils in Halpha images of solar observations. Our method consists of a data pre-processing comp…
astro-ph.SR2020★ 15 cited
Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning
Haodi Jiang, Jiasheng Wang, Chang Liu +4
Deep learning has drawn a lot of interest in recent years due to its effectiveness in processing big and complex observational data gathered from diverse instruments. Here we propo…