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Author

Jun Lin

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2026

Seismic Random Noise Attenuation via Implicit Neural Representations With Multiple Structural Priors

Seismic data are inevitably contaminated by random noise arising from various sources, which seriously degrades the quality of subsequent data processing, inversion, and interpretation. Deep learning has emerged as an effective approach for seismic random noise attenuation. However, these methods are often susceptible...

Yun-Hong Wang, Rui-Hua Chen, Jun Lin et al. · 0 citations
2026

Category-Level Positive–Negative Prompting for Open-Set Cross-Scene Remote Sensing Image Classification

Cross-scene remote sensing (RS) image classification is crucial for urban analysis and environmental monitoring, but often suffers from distribution shifts caused by different imaging conditions. While unsupervised domain adaptation (UDA) can alleviate cross-scene discrepancies, its closed-set assumption is violated wh...

Xin Zhao, Yuanyuan Ye, Jun Lin et al. · 0 citations

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