LifeCLEF Bird Identification Task 2017

Based on virus antigen expression, intesti- nal epithelium expressed 2016 H5N8 antigen in four of twelve bird species (5 of 29 individual birds, excluding 10 unspecified ducks)

The BirdCLEF challenge—as part of the 2019 LifeCLEF Lab [7]—offers a large-scale proving ground for system-oriented evaluation of bird species identification based on audio

Meanwhile, a dampening factor of 0 to 0.5 are multiplied for each noise file .(In [9], the greatest impact on identification performance is gained by adding background noise.

With additional methods like filtering audio chunks with random transfer function or applying local time stretching and pitch shifting in time domain, identification

Inception-based architectures perform very well: As previous year, the best performing system of the challenge is based on an Inception architec- ture, in particular the Inception

Assessing high-quality field recordings for the presence of bird species using con- volutional neural networks is an effective application of deep learning techniques to the domain

Section 2 details the layout and training of a Convolutional Neural Network (CNN) processing the audio signals, Section 3 describes a Multilayer Perceptron (MLP) predicting the

The main novelty of the 2017 edi- tion of BirdCLEF was the inclusion of soundscape recordings containing time-coded bird species annotations in addition to the usual