Design and Performance Evaluation of a Deep Neural Network for Spectrum Recognition of Underwater Targets
Due to the complexity of the underwater environment, underwater acoustic target recognition (UATR) has always been challenging. Although deep neural networks (DNN) have been used in UATR and some achievements have been made, the performance is not satisfactory when recognizing underwater targets wit...
Main Authors: | Dali Liu, Xuchen Zhao, Wenjing Cao, Wei Wang, Yi Lu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2020-01-01
|
Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2020/8848507 |
Similar Items
-
A Deep Convolutional Neural Network Inspired by Auditory Perception for Underwater Acoustic Target Recognition
by: Honghui Yang, et al.
Published: (2019-03-01) -
Underwater Acoustic Target Recognition: A Combination of Multi-Dimensional Fusion Features and Modified Deep Neural Network
by: Xingmei Wang, et al.
Published: (2019-08-01) -
Underwater Target Recognition Based on Improved YOLOv4 Neural Network
by: Lingyu Chen, et al.
Published: (2021-07-01) -
Sonar image recognition of underwater target based on convolutional neural network
Published: (2021-04-01) -
Underwater Acoustic Target Recognition Based on Depthwise Separable Convolution Neural Networks
by: Gang Hu, et al.
Published: (2021-02-01)