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arXiv AI By Nathaniel Chen, Kouroche Bouchiat, Peter Steiner, Andrew Rothstein, David Smith, Max Austin, Mike van Zeeland, Marie Roch, Azarakhsh Jalalvand, Egemen Kolemen

A general extractor for coherent patterns across time-frequency measurements

Read the original on arXiv AI →

The paper introduces TokEye, a reference‑free method that learns a general criterion for coherent structure from heterogeneous time‑frequency measurements. Without retraining, TokEye can extract signals from diverse fields such as marine bioacoustics and wideband radar, achieving high recovery rates (82.5% for stellarator signals, 78% for dolphin whistles, and 81.5% average precision on radar benchmarks). The method processes full experimental spectrograms in under one second on a GPU, demonstrating scalable automated scientific signal discovery across unrelated sensors.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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