Year: 2011
Type: article
Abstract: also developed.Features extracted from proposed algorithms were then combined with various classification algorithms such as k-NN, Multilayer Perceptron (MLP) and Hidden Markov Models (HMM) and Evolutionary Neural Network (ENN).SIFS and MMS algorithms, combined with ENN and MLP, provided the most accurate results.Proposed algorithms were tested with real data collected during the spring migration, around Lake Erie in Ohio, of five nocturnally migrating bird species native to Northwest Ohio.Also, sparrows, warblers and thrushes passing over the University of Toledo, the Ottawa National Wildlife Refuge and Ohio State University's Stone Lab between April 20 -May 29 were calculated.Quantification of class level migratory bird has been presented.The developed bird flight call recognition system is suitable for deployment for both onshore & off-shore wind turbine locations.This system would be suitable for 24/7 remote sensing.v
Author: Selin Bastas
Institution: University of Toledo
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Award: G8345182385
OpenAlex ID: W1854687441