Author

Bo-Wen Huang

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Open access Sep 2026

Toward Optimal Photometric Calibration of Digital Astronomical Plates with Deep Learning

A deep learning calibration framework, the Multi-Feature Fused Network (MFF-Net), is introduced, which takes instrumental magnitude, color, and pixel coordinates as input and learns a single nonlinear correction that jointly captures their coupled dependencies.

M. Ma, Hai-Bo Yuan, Lin Yang et al. · Astrophysical Journal Supple... · 0 citations

Preprint Aug 2026

Towards optimal photometric calibration of digital astronomical plates with deep learning

Photometric calibration of digitized photographic plates is commonly modeled with separable magnitude-, color-, and position-dependent terms, but this separability can break down when image quality varies across the field in a magnitude-dependent way, leaving coupled spatial systematics in the residuals. We introduce a...

M. Ma, Hai-Bo Yuan, Lin Yang et al. · 0 citations