RouteGraph-Mona: Confusion-Aware Routing Fine-Tuning for Mineral Image Classification
Read the original on arXiv AI →RouteGraph-Mona introduces a confusion‑aware routing fine‑tuning approach for mineral image classification, building on the Mona visual adapter. It replaces Mona’s static multi‑scale aggregation with sample‑adaptive routing, creating a compact routing space that reflects each image’s scale preferences. The method regularizes routing signatures using class‑wise route anchors and confusion‑weighted margins, encouraging consistent routing patterns and greater separation between visually similar mineral categories. Experiments on three public mineral image datasets with two visual backbones show that RouteGraph‑Mona consistently outperforms Mona and remains competitive with other fine‑tuning methods and classification baselines.
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