A Transfer Learning Strategy for Owl Sound Classification by Using Image Classification Model
Accurately predicting an owl species based on its sound can be helpful for owl conservation. To build an accurate model for owl sound classification, deep learning is currently the most preferred algorithm, due to its excellent performance for modeling audio data. However, deep learning is generally underperformed for a small dataset, which is the case for recognizing scops owl sound. To overcome the issue, we proposed a transfer learning strategy that can alleviate overfitting in a deep learning model for the owl sound classification. Our strategy enables the use of a pretrained image classification model, which is widely available, for transfer learning in owl sound classification.
International Conference on Eco Engineering Development 2020
Kevin William Gunawan, Alam Ahmad Hidayat, Tjeng Wawan Cenggoro, and Bens Pardamean
