Variational Encoder-Decoder Recurrent Neural Network (VED-RNN) for Anomaly Prediction in a Host Environment.
Lydia Bouzar-BenlabiodLila MézianiStuart H. RubinKahina BelaidiNour El Houda HaddarPublished in: IRI (2019)
Keyphrases
- recurrent neural networks
- chaotic time series
- neural network
- low complexity
- feed forward
- video codec
- decoding process
- motion compensated prediction
- hidden layer
- recurrent networks
- complex valued
- neural model
- reservoir computing
- long short term memory
- artificial neural networks
- distributed video coding
- video coding
- error resilience
- echo state networks
- error control
- rate distortion
- wyner ziv video coding
- video coding scheme
- prediction error
- artificial intelligence
- distributed source coding
- optical flow
- wyner ziv
- bit rate
- anomaly detection
- motion compensated
- motion estimation
- fuzzy logic
- error resilient
- noisy channel
- image sequences
- inter frame