Event Detection

It is the task of identify only one signal of interest among variety of recorded events.

The task of identifying one seismic event of interest among all different types of signals and noise recorded by a seismometer. Here we differentiate between event discrimination (i.e. a task of identifying multiple classes of signal of interests) and event detection (i.e. the binary classification task of identifying the event and non-event signals).

Used ML Approaches:

  • Artificial Neural Networks

  • Support Vector Machine

  • Dynamic Bayesian Networks

  • Random Forest

  • Hidden Markov Model

  • K-Nearest Neighbors

  • Decision Tree

  • Dictionary Learning

  • Gaussian Process

Used Neural Networks:

  • FC

  • RNN

  • CNN

  • GAN

  • LSTM

  • TCN

  • GRU

  • Attention

  • 'VGG

  • YOLO

  • U-Net

  • LeNet

  • Transformer

  • ResNet

  • CapsNet

  • Siamese

  • GoogleNet

  • AlexNet

  • SqueezeNet

Used Learning Procedures:

  • Supervised Learning

  • Reinforcement Learning

  • Unsupervised Learning

  • Transfer Learning

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