Can a neural net be trained to solve this problem?
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Lowell Bartlett 2021년 7월 26일
댓글: Lowell Bartlett 2021년 8월 5일
We are interested in exploring Matlab's deep learning toolbox to solve analog seismogram records. An example seismogram image with seismic traces is shown below. The traces are time series data. In all images, the center of the traces have been identified (the red lines) and saved elsewhere as x-y raster data. These data are necessarily disconnected from one another (i.e. there are always gaps in the data). In addition to the traces, the so-called mean lines - the zero energy line about which the traces oscillate - are also identified. The challenge is to associate each trace segment with its appropriate mean line. Some are easy, but during seismic activity it can be seen that traces can cross multiple mean lines.
We have access to a potentially large number of training set data, and would like to understand if this training data could be used to train a deep learning network.
Thanks for any suggestions as to how we might begin to investigate this problem. Please feel free to check out the image and data set at seismo.redfish.com.
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Swetha Polemoni 2021년 7월 29일
It is my understanding that you want to categorise trace segment to its mean line(class). You can use Classification for these kind of problems. Hope you find this helpful.
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