RAVEN X High Performance Data Mining Toolbox for Bioacoustic Data Analysis
Not on the map. Why?
Abstract (arXiv)
Objective of this work is to integrate high performance computing (HPC) technologies and bioacoustics data-mining capabilities by offering a MATLAB-based toolbox called Raven-X. Raven-X will provide a hardware-independent solution, for processing large acoustic datasets - the toolkit will be available to the community at no cost. This goal will be achieved by leveraging prior work done which successfully deployed MATLAB based HPC tools within Cornell University's Bioacoustics Research Program (BRP). These tools enabled commonly available multi-core computers to process data at accelerated rates to detect and classify whale sounds in large multi-channel sound archives. Through this collaboration, we will expand on this effort which was featured through Mathworks research and industry forums incorporate new cutting-edge detectors and classifiers, and disseminate Raven-X to the broader bioacoustics community.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 12 Oct 2016.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 1.
1 paper.