Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

This project uses a Keras/TensorFlow Autoencoder to identify anomalous traffic patterns in an AWS Elastic Load Balancer (ELB) request count dataset. The goal is to build an unsupervised learning model ...

We propose Scenario Dreamer, a fully data-driven closed-loop generative simulator for autonomous vehicle planning. If you'd prefer to skip data extraction and preprocessing, you can directly download ...

Microphone Array,Convolutional Layers,Compact Array,Direction Of Arrival,Neural Network,Short-time Fourier Transform,Clear Speech,Deep Neural Network,Feature Dimension,Mel-frequency Cepstral ...