1.Internet is flooded with Textual data. 2.The internet age has brought unfathomably massive amounts of information to the fingertips of billons - if only we had time to read it. 3.Text summarization helps to direct people's attention to the most important contents and saves tremendous human labor for digging through the documents.
We present a robust classification approach for avian vocalization in complex and diverse soundscapes. We illustrate how to make full use of pre-trained convolutional neural networks, by using an efficient modeling and training routine supplemented by novel augmentation methods. Thereby, we improve the generalization of weakly labeled crowd-sourced data to productive data collected by autonomous recording units. As such, we illustrate how to progress towards an accurate automated assessment of avian population which would enable global biodiversity monitoring at scale, impossible by manual annotation.