Search Results for author:
Found 4 papers, 0 papers with code
Using system context information to complement weakly labeled data
Real-world datasets collected with sensor networks often contain incomplete and uncertain labels as well as artefacts arising from the system environment.
Event-triggered Natural Hazard Monitoring with Convolutional Neural Networks on the Edge
Decision making at the edge of a wireless sensor network promises fast response times but is limited by the availability of energy, data transfer speed, processing and memory constraints.
Unsupervised Feature Learning for Audio Analysis
It incorporates the two following novel contributions: First, an audio frame predictor based on a Convolutional LSTM autoencoder is demonstrated, which is used for unsupervised feature extraction.
Efficient Convolutional Neural Network For Audio Event Detection
Wireless distributed systems as used in sensor networks, Internet-of-Things and cyber-physical systems, impose high requirements on resource efficiency.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
