Towards Filament Segmentation Using Deep Neural Networks

Abstract. We use a well-known deep neural network framework, called Mask R-CNN, for identification of solar filaments in full-disk H-α images from Big Bear Solar Observatory (BBSO). The image data, collected from BBSO's archive, are integrated with the spatiotemporal metadata of filaments retrieved from the Heliophysics Events Knowledgeable (HEK) system. T ... [more]

Nov 20, 2019

Challenges with Extreme Class-Imbalance Issue

In analyses of rare-events, regardless of the domain of application, class-imbalance issue is intrinsic. Although the challenges are known to data experts, their explicit impact on the analytic and the decisions made based on the findings are often overlooked. This is in particular prevalent ... [more]

Nov 20, 2019

An Image-Parameter Dataset from Solar Dynamics Observatory Mission

We provide a large image parameter dataset extracted from the Solar Dynamics Observatory (SDO) mission’s AIA instrument, for the period of January 2011 through the current date, with the cadence of six minutes, for nine wavelength channels. The volume of the dataset for each year is just short of 1 TiB. Towards achieving ... [more]

Jul 19, 2019