Activity Recognition and Abnormal Behaviour Detection with Recurrent Neural Networks

Abnormal Heartbeat Detection Using Recurrent Neural Networks

The observation and management of cardiac features (using automated cardiac auscultation) is of significant interest to the healthcare community. In this work, we propose for the first time the use of recurrent neural networks (RNNs) for automated cardiac auscultation and detection of abnormal heartbeat detection. The application of RNNs for this task is compelling since RNNs represent the deep...

Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks

This work proposes a simple pipeline to classify and temporally localize activities in untrimmed videos. Our system uses features from a 3D Convolutional Neural Network (C3D) as input to train a a recurrent neural network (RNN) that learns to classify video clips of 16 frames. After clip prediction, we post-process the output of the RNN to assign a single activity label to each video, and deter...

Recurrent neural networks for object detection and motion recognition!

Audio Chord Recognition with Recurrent Neural Networks

In this paper, we present an audio chord recognition system based on a recurrent neural network. The audio features are obtained from a deep neural network optimized with a combination of chromagram targets and chord information, and aggregated over different time scales. Contrarily to other existing approaches, our system incorporates acoustic and musicological models under a single training o...

Speaker recognition with recurrent neural networks

We report on the application of recurrent neural nets in a openset text-dependent speaker identification task. The motivation for applying recurrent neural nets to this domain is to find out if their ability to take short-term spectral features but yet respond to long-term temporal events is advantageous for speaker identification. We use a feedforward net architecture adapted from that introdu...