An Edge-Optimized Incremental Learning Algorithm For Audio Classification

Tsung Han Tsai, Muhammad Awais Hussain, Chun Lin Lee

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

In the proposed demo, we would like to show the incremental learning for audio classification using an embedded system. Figure 1 shows the overview of the data processing based on our proposed incremental learning algorithm. The proposed incremental learning algorithm can increase the capability of DNN model to classify new audio sounds which are not included in the base model. In the proposed system, the audio data is gathered at the edge device, and DNN model is trained using our proposed algorithm to learn about the new classes while retaining the knowledge about previous classes as well.

原文???core.languages.en_GB???
主出版物標題Proceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
發行者Institute of Electrical and Electronics Engineers Inc.
頁面504
頁數1
ISBN(電子)9781665409964
DOIs
出版狀態已出版 - 2022
事件4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022 - Incheon, Korea, Republic of
持續時間: 13 6月 202215 6月 2022

出版系列

名字Proceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022

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???event.eventtypes.event.conference???4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
國家/地區Korea, Republic of
城市Incheon
期間13/06/2215/06/22

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