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Identification of Magnetic Reconnection in Plasma Turbulence Using a Dual-branch Lightweight Hybrid Convolutional Neural Network

Authors: Y. Yin, S. Y. Huang, Q. Y. Xiong, H. Zhang, Z. G. Yuan, K. Jiang, H. H. Wu, H. W. Zhan, Y. T. Tang, H. Bai

Y. Yin et al 2026 The Astrophysical Journal Supplement Series 287 .

Provider: AAS Journals

Caption: Figure 9.

Comparative performance of six models across five metrics. This line chart illustrates the (M, T, R, S, A) scores for each model, where a higher value denotes better performance. The models and their line styles are: DHCNN-64 (solid red), HCNN-P-64 (green dashed–dotted), HCNN-N-64 (dotted blue), HCNN-A-64 (solid purple), CNN-32 (dashed orange) and decision tree (pink dashed–dotted).

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