activity
20152025
most citedPrediction of Solar Flare Size and Time-to-Flare Using Support Vector Machine Regression

48 citations · 181 across the 12 of their papers we have counts for

collaborators

13 papers

astro-ph.SR2025

Incorporating Magnetic Field Characteristics into EUV-Based Automated Segmentation of Coronal Holes

Jeremy A. Grajeda, Laura E. Boucheron, Michael S. Kirk +3

Coronal holes (CHs) are magnetically open regions that allow hot coronal plasma to escape from the Sun and form the high-speed solar wind. This wind can interact with Earth's magne…

astro-ph.SR2024★ 3 cited

Magnetic Field-Constrained Ensemble Image Segmentation of Coronal Holes in Chromospheric Observations

Jaime A. Landeros, Michael S. Kirk, C. Nick Arge +5

Coronal Holes (CHs) are large-scale, low-density regions in the solar atmosphere which may expel high-speed solar wind streams that incite hazardous, geomagnetic storms. Coronal an…

eess.IV2024★ 3 cited

Estimation of non-uniform motion blur using a patch-based regression convolutional neural network (CNN)

Luis G. Varela, Laura E. Boucheron, Steven Sandoval +2

The non-uniform blur of atmospheric turbulence can be modeled as a superposition of linear motion blur kernels at a patch level. We propose a regression convolutional neural networ…

eess.IV2023★ 7 cited

Neural-based Compression Scheme for Solar Image Data

Ali Zafari, Atefeh Khoshkhahtinat, Jeremy A. Grajeda +6

Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them eff…

astro-ph.SR2023★ 8 cited

Quantifying the Consistency and Characterizing the Confidence of Coronal Holes Detected by Active Contours without Edges (ACWE)

Jeremy A. Grajeda, Laura E. Boucheron, Michael S. Kirk +2

Coronal Holes (CHs) are regions of open magnetic field lines, resulting in high speed solar wind. Accurate detection of CHs is vital for space weather prediction. This paper presen…

eess.IV2023★ 8 cited

Estimation of motion blur kernel parameters using regression convolutional neural networks

Luis G. Varela, Laura E. Boucheron, Steven Sandoval +2

Many deblurring and blur kernel estimation methods use a maximum a posteriori (MAP) approach or deep learning-based classification techniques to sharpen an image and/or predict the…