Low-light image enhancement (LLIE) requires a practical balance among visibility recovery, reconstruction fidelity, chromatic stability, exposure safety, and computational efficiency. Aggressive enhancement can reveal dark content but may introduce highlight saturation and color distortion, whereas conservative enhance...
Tao Jiang, Su-Hang Yang, Yu-Chen Lu et al.· Journal of King Saud Univers...· 0 citations
Accurate traffic-flow forecasting remains challenged by abrupt and irregular states even after dominant periodic patterns are captured. Existing predictors model the resulting difficult errors implicitly through their parameters and cannot explicitly reuse specific historical errors at inference. We find that multi-hor...
Qian-Xin Xie, Jin-Feng Xu, Yu-Chen Lu et al.· Mathematics· 0 citations
RIFT-STGNN, a Robust Interleaved Frequency–Trend Spatio-Temporal Graph Neural Network for multi-step traffic flow forecasting, follows a coordinated information flow and shows competitive numerical performance relative to selected literature-reported baselines under the 12-step setting.
Qian-Xin Xie, Jin-Feng Xu, Yuchen Lu et al.· Mathematics· 1 citation
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