titu1994/LSTM-FCN
Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification
This project helps scientists, engineers, and analysts accurately categorize time-series data, like sensor readings or financial trends. It takes raw time-series measurements as input and outputs a classification that tells you what 'type' of event or pattern that series represents. This is useful for anyone needing to automatically identify specific behaviors or conditions from sequential data.
804 stars. No commits in the last 6 months.
Use this if you need to classify time-series data, especially if you're looking for a model that combines the strengths of both convolutional and recurrent neural networks for high accuracy.
Not ideal if your data is not time-series or if you are looking for a simple, out-of-the-box solution without any programming, as this requires a developer to implement.
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804
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265
Language
Python
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Last pushed
Mar 01, 2019
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