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IEEE/ICACT20260373 Slide.03
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However, the transition to deep learning brings a critical challenge known as the "Small-Sample Problem". Although deep learning models demand massive labeled datasets to function effectively, obtaining such datasets for echo signals is expensive and logistically difficult, and real-world signals are often corrupted by environmental noise. Consequently, standard models trained on limited data tend to overfit or fail to generalize to new environments. | |
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