Convolutional Neural Network for Sound Processing - Study of Deployed Application

P. Doležel, Dominik Stursa, Daniel Honc
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Abstract

Pest birds are considered as a special kind of vermin, since, in most of countries, their legal position does not enable their direct extermination. Therefore, in order to protect the agricultural areas indirectly from pest birds, the robust and highly selective pest bird sensor is necessary to design. In this contribution, the pest bird detection unit, based on a convolutional neural network, is presented. The convolutional neural network itself is used for the decision making about the pest bird occurrence, while sound recordings are used as input data. The testings, presented at the end of the contribution, proved a very high accuracy of the detection unit, with the results indispensably improved in comparison to previously presented approaches.
卷积神经网络在声音处理中的应用研究
害虫鸟被认为是一种特殊的害虫,因为在大多数国家,它们的法律地位不允许直接消灭它们。因此,为了间接保护农区免受有害鸟类的侵害,有必要设计鲁棒性和高选择性的有害鸟类传感器。在这篇贡献中,提出了基于卷积神经网络的害虫鸟检测单元。卷积神经网络本身用于害虫鸟发生的决策,而声音记录用作输入数据。在贡献结束时提出的测试证明了检测单元的非常高的准确性,与以前提出的方法相比,结果得到了不可缺少的改进。
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