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Temporal feature interaction and fusion for multi-modal information: a semi-supervised soft-sensor framework for the iron ore sintering process
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DOI：10.1016/j.measurement.2026.122811.png)
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Abstract
En 中文
• Propose a TFIF-ssTransformer soft-sensor framework for sintering process. • Fuse time-series and thermal images for accurate FeO content prediction. • Use entropy-regularized cosine similarity for temporal feature interaction. • Achieve up to 27.8% RMSE reduction over benchmarks in sparse labeling regimes.
Keywords:
Soft Sensor
Multi-modal Fusion
Semi-supervised Learning
Temporal Feature Interaction
Iron Ore Sintering
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