Historical Manchu documents preserve invaluable linguistic and cultural heritage, yet their digitization is hindered by severe degradations and the scarcity of paired training data. Existing document restoration methods primarily optimize pixel-level reconstruction, which can produce visually plausible results while fa...
T. Huang, Dongdong Wang, Ming-Qiu Liang et al.· 0 citations
SAGE-Restore (Stroke-Aware Gated rEstoration), a selective restoration framework that first assesses where restoration is needed and then uses this assessment to guide restoration candidate generation and pixel-level selection, is proposed.
Ming-Qiu Liang, Dongdong Wang, Si-Yang Lu et al.· 0 citations
A systematic empirical analysis across three public log datasets, examining different adaptation strategies, model architectures, parameter scales, and quantization settings reveals substantial performance differences across adaptation strategies, while model scaling yields varying detection gains across datasets.
TPpred-PepPA is developed, a two-stage hierarchical deep learning framework based on the ProtT5 pre-trained large language model that achieves state-of-the-art predictive performance and provides valuable interpretability for the discovery of multi-functional therapeutic peptides.
Ke Yan, Si-Yang Lu, Shutao Chen et al.· BMC Biology· 0 citations
Log Reconstruction and Distance (LoRD), a lightweight post-hoc calibration framework for reliable log anomaly detection, is proposed and demonstrates that LoRD consistently improves confidence reliability and substantially reduces overconfident anomaly-related errors without sacrificing anomaly detection performance.
Bin Li, Dongdong Wang, Si-Yang Lu· 0 citations
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