Performance comparison of CNN models with different input features.

Performance comparison of CNN models with different input features.

<p>Performance comparison of CNN models with different input features.</p>

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Bibliographic Details
Main Author:	Dongmei Liu (268523) (author)
Other Authors:	Junsong Zhang (5157851) (author), Bingrui Zhao (17137234) (author), Linsheng Gao (22478134) (author), Hao Zhou (136535) (author), Zhiheng Cheng (10159466) (author), Liang Chen (73736) (author), Meichen Li (8773820) (author)
Published:	2025
Subjects:	Biophysics Cell Biology Neuroscience Biological Sciences not elsewhere classified Information Systems not elsewhere classified study innovatively introduces seam boreholes generates g ., short capture comprehensive spatiotemporal 72 %, outperforming 10 different degrees network degree distribution 546 effective waveforms dimensional cnn model cnn ), integrating weak microseismic signals misjudging background noise mine microseismic signals analyze microseismic signals identical precision rate higher recall rate propagation dynamics model microseismic event identification fourier cnn model dynamic signal characteristics domain cnn model domain features enables background noise data computational communication concepts cnn model microseismic signals background noise recall rate precision rate propagation network microseismic data domain waveforms noise ratios adding noise fourier images computational propagation computational communication communication technology integrating time frequency characteristics domain images domain features xlink "> subsequent positioning snr ). performing translation new path mining field low signal large number
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Summary:	<p>Performance comparison of CNN models with different input features.</p>

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