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The XAI-assisted Recurrent neural network Attribution for Channel Estimation (X-RACE) framework is proposed, and novel temporal XAI metrics: Saturation Time, Importance Drift, and Relevance Contrast are proposed to characterize the LSTM's learning dynamics and memory convergence.
An entropy-centric approach to explainable AI significantly enhances the interpretability of semantic segmentation in remote sensing, outperforming existing methods.