Name
Abstract | ||
|---|---|---|
Reliable identification of bird species in recorded audio files would be a transformative tool for researchers, conservation biologists, and birders. In recent years, artificial neural networks have greatly improved the detection quality of machine learning systems for bird species recognition. We present a baseline system using convolutional neural networks. We publish our code base as reference for participants in the 2018 LifeCLEF bird identification task and discuss our experiments and potential improvements. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computer Vision and Pattern Recognition | Transformative learning,Computer science,Convolutional neural network,Artificial intelligence,Baseline system,Artificial neural network,Machine learning |
DocType | Volume | Citations |
Journal | abs/1804.07177 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefan Kahl | 1 | 0 | 8.79 |
| Thomas Wilhelm-Stein | 2 | 62 | 10.41 |
| Holger Klinck | 3 | 0 | 2.03 |
| Danny Kowerko | 4 | 0 | 3.72 |
| Maximilian Eibl | 5 | 119 | 37.66 |