Deep Learning in Solar Astronomy by Long Xu & Yihua Yan & Xin Huang

Author:Long Xu & Yihua Yan & Xin Huang
Language: eng
Format: epub
ISBN: 9789811927461
Publisher: Springer Nature Singapore

Algorithms

Related work

Threshold

Morphology

Region growing

Clustering

Deep learning

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Deep learning method has been proposed to learn a detection model from the observational data, including R-CNN, Fast R-CNN, Faster R-CNN and more new algorithms. There are three steps to generate a R-CNN detector. In first step, region proposals are generated. And then, a CNN is trained to classify these proposal regions. Finally, the bounding boxes of the proposal regions are refined. Unlike the R-CNN algorithm, fast R-CNN algorithm maps CNN features corresponding to generated region proposals, hence, the fast R-CNN detector is more efficient than the R-CNN detector. In Faster R-CNN detector, region proposal network (RPN) is used to generate region proposals. RPN is faster and better than the proposed generation method of region proposals. In this paper, we implement a deep learning based active region detection model for the first time.

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