DTRNet: Dual Text-Radical Decoding for Handwritten Chinese Text Recognition with Faked Character Detection
DTRNet is proposed, a dual Text-Radical decoding framework for line-level faked character detection and IDS-Guided Confidence Adjustment (IGCA) is introduced to refine text predictions using structural evidence during inference to preserve character-structural evidence independent of contextual inference.