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 # ClusTremor
 ClusTremor is an algorithm specifically designed for unsupervised clustering of seismic data, with a focus on tremor signals. Leveraging the power of deep learning and clustering techniques, we employ a deep clustering approach to effectively cluster volcanic tremors.
 
-![Eruptive phases](https://github.com/ZahraZali/ClusTremor/assets/50201021/1fc405fd-3c73-431a-a816-0eb94c68d4c0)
+![Eruptive phases](https://github.com/ZahraZali/ClusTremor/assets/50201021/3e18f907-7dae-41cf-8ee1-cc869eac33c4)
 
 Our methodology utilizes an autoencoder, allowing the model to learn meaningful feature representations while assigning clusters to them. This joint learning process ensures the extraction of informative representations that capture the underlying patterns in tremor signals and effectively cluster them.