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cnn-lstm-models

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The project is a concoction of research (audio signal processing, keyword spotting, ASR), development (audio data processing, deep neural network training, evaluation) and deployment (building model artifacts, web app development, docker, cloud PaaS) by integrating CI/CD pipelines with automated tests and releases.

  • Updated Sep 4, 2022
  • PureBasic

Hybrid CNN-LSTM deep learning model for electrical fault classification in power transmission lines. Achieves 78% accuracy across 6 fault types using time-series analysis. Includes complete ML pipeline with preprocessing, training, and evaluation tools. Built with TensorFlow & Keras.

  • Updated Feb 14, 2026
  • Python

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