Feb 6, 2021 · We propose an explainable convolutional neural network XTF-CNN that supplies both excellent classification performance and explainability.

Feb 21, 2025 · Bi et al. [104] introduced a CNN for microseismic event waveform classification, surpassing state-ofthe-art ML methods in recall and accuracy.

A precise model for identifying and classifying microseismic signals based on deep learning technology and short-time Fourier transform (STFT) technology is ...

We have determined why CWT-CNN has better performance for noisy microseismic data. CWT can decompose the microseismic data into time-frequency spectra, where ...

Xin et al. (2021) [19] proposed an explainable time-frequency convolutional neural network (CNN) to provide an excellent classification performance and ...

Missing: Explainable | Show results with:Explainable

Apr 27, 2023 · An improved model which is suitable for microseismic (MS) monitoring waveform recognition was proposed in this study based on the LeNet framework.

Missing: Explainable | Show results with:Explainable

This paper employs a literature review approach to summarize the research progress on microseismic signal identification methods and techniques over the past ...

Oct 31, 2024 · Ma, ''Explainable time–frequency convolutional neural network for microseismic waveform classification,'' Inf. Sci., vol. 546, pp. 883–896 ...