Birds have always been important part of every surroundings and they are utmost important
to the environment. Taking this, it's now clear that how important and is required it is to be …

Birds are crucial to the ecosystem's optimum functioning since they maintain a stable
climate, convert toxins into nutrients, and oxygenate the atmosphere. Identifying multiple bird …

The paper uses an attention-based framework to classify bird vocalizations in real-time
audio recordings. Transformers have recently demonstrated exemplary performance on …

Birdsong detection with machine learning (ML) models can provide valuable insights for
informed decision making in conservation efforts. Previous methods usually convert audio to …

Identification of bird species through automatic analysis of their vocalizations holds great
promise for various fields, such as ecology, conservation monitoring, and vocal behavioural …

Birds significantly contribute to ecosystem maintenance, involving seed dispersion, air
oxygenation, contaminant conversion into nutrients, and climate regulation. However, with …

Automated classification of bird sounds plays an im-portant role in monitoring and protecting
biodiversity. Recently, similar efforts have been carried out for birds from all over the world …

This study is about building a Convolutional Neural Network (CNN) model with TensorFlow
to tackle the challenge of quantifying the density of Capuchin bird calls in audio clips. The …

Birds are excellent bioindicators, playing a vital role in maintaining the delicate balance of
ecosystems. Identifying species from bird vocalization is arduous but has high research …

Birds have an enormous impact on the ecosystem and various information about an area
can be produced from the bird species prevalent in it. Ornithologists have been monitoring …