• Published 2016

Automated Mouse Behavior Recognition using VGG Features and LSTM Networks

@inproceedings{Kramida2016AutomatedMB,
  title={Automated Mouse Behavior Recognition using VGG Features and LSTM Networks},
  author={Gregory Kramida and Yiannis Aloimonos and Cornelia Ferm{\"u}ller and Nikolas A Francis},
  year={2016}
}
We present a mouse behavior classification method using a recurrent neural network with the long short-term memory (LSTM) model. The experimental hardware used to collect the data is a custom mouse cage with four stereo-camera pairs in each wall. Using as input the different videos, our computational method employs a so-called end-to-end learning approach: visual features from pre-trained convolutional neural networks are extracted from each image frame, and used to train a customized LSTM… CONTINUE READING

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