"DeepShip: An underwater acoustic benchmark dataset and a separable ..."

Muhammad Irfan et al. (2021)

> Home

Details and statistics

DOI: 10.1016/J.ESWA.2021.115270

access: closed

type: Journal Article

metadata version: 2024-10-06

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/eswa/IrfanZAIMH21
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/eswa/IrfanZAIMH21
Muhammad Irfan, Jiangbin Zheng, Shahid Ali, Muhammad Iqbal, Zafar Masood, Umar Hamid:
DeepShip: An underwater acoustic benchmark dataset and a separable convolution based autoencoder for classification. Expert Syst. Appl. 183: 115270 (2021)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.