Open-Set Recognition for Deep Neural Networks-based Underwater Acoustic Target Classification
Author:
Affiliation:
1. Institute of Acoustics, Chinese Academy of Sciences,State Key Laboratory of Acoustics,Beijing,China,100190
2. Université Bourgogne Franche-Comté,ImViA EA7535,Dijon,France,21078
Funder
Chinese Academy of Sciences
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9705657/9705658/09705688.pdf?arnumber=9705688
Reference21 articles.
1. Machine learning in acoustics: Theory and applications
2. Neural-Network-Based Classification of Commercial Ships From Multi-Influence Passive Signatures;axelsson;IEEE Journal of Oceanic Engineering,2020
3. Underwater Acoustic Target Classification Based on Dense Convolutional Neural Network;doan;IEEE Geoscience and Remote Sensing Letters,2020
4. The underwater acoustic target timbre perception and recognition based on the auditory inspired deep convolutional neural network
5. Recognition of imbalanced underwater acoustic datasets with exponentially weighted cross-entropy loss
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