A research on underwater target recognition neural network for small samples
In the face of the challenges in the field of marine engineering applications in the new era, the goal of automation, high efficiency and accuracy can be achieved by using deep learning-based neural networks in hydroacoustic engineering. However, in the face of objective problems such as the lack of...
Main Authors: | WU Yanchen, WANG Yingmin |
---|---|
Format: | Article |
Language: | zho |
Published: |
EDP Sciences
2022-02-01
|
Series: | Xibei Gongye Daxue Xuebao |
Subjects: | |
Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2022/01/jnwpu2022401p40/jnwpu2022401p40.html |
Similar Items
-
STM: Spectrogram Transformer Model for Underwater Acoustic Target Recognition
by: Peng Li, et al.
Published: (2022-10-01) -
Underwater Acoustic Target Recognition Based on Depthwise Separable Convolution Neural Networks
by: Gang Hu, et al.
Published: (2021-02-01) -
A Novel Deep Learning Method for Underwater Target Recognition Based on Res-Dense Convolutional Neural Network with Attention Mechanism
by: Anqi Jin, et al.
Published: (2023-01-01) -
Generalizable Underwater Acoustic Target Recognition Using Feature Extraction Module of Neural Network
by: Daihui Li, et al.
Published: (2022-10-01) -
YOLOv5s-CA: A Modified YOLOv5s Network with Coordinate Attention for Underwater Target Detection
by: Ge Wen, et al.
Published: (2023-03-01)