Deep Learning Based Audio Classifier for Bird Spcies
Aarti Anant Madhavi
, Rajani Pamnani
Convolutional Neural Networks, Deep Residual Neural Network, Bird Species Classification, Data Augmentation
The effect of human activities on the environment has reached a point where it has become necessary to track the effects before it causes irreparable damage to the environment. One of the ways to track such effects is to monitor the breeding behaviour, biodiversity and population dynamics of animals. Birds are one of the best species to track as they do tend to be the most reactive ones for any change in the environment e.g., deforestation or forest fires. Till now, the tracking of the birds was done manually by experts, which is very tedious at the same time consuming and non-viable method. As a result to alleviate this issue and provide assistance to the ecologists we proposing a machine learning method to recognize the bird's species based on the audio recordings. To achieve this goal, we intend to use the state of art convolutional neural network architecture called the deep residual neural networks as compared to the traditionally used classifiers like SMACPY, SVM and other relatively less sophisticated
"Deep Learning Based Audio Classifier for Bird Spcies", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 10, page no.228 - 233, October-2018, Available :https://ijsdr.org/papers/IJSDR1810037.pdf
Volume 3
Issue 10,
October-2018
Pages : 228 - 233
Paper Reg. ID: IJSDR_180730
Published Paper Id: IJSDR1810037
Downloads: 000347228
Research Area: Engineering
Country: Panvel, Navi Mumbai, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
