Pollinating insects are important for agriculture and ecological flourishing, but they are difficult to monitor, as identification is tricky, labor-intensive, and typically requires killing some insects. Publishing in PNAS Nexus, Adam Narbudowicz and colleagues use machine learning to identify insects by the changes in their radar reflection, caused by the flapping of their wings. The machine learning model extracted more than 70 harmonic, spectral, and temporal features from the Doppler radar signatures.
DAMPE satellite reveals cosmic rays share spectral break near 15 teravolts
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