PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
Marine pollution is a major environmental hazard and a serious healthcare, economic, and social issue. Machine learning (ML) and deep learning (DL) techniques can be used to automate marine waste removal and make the cleanup process more efficient. The proposed study uses image classification to help categorize the level of marine pollution in ocean underwater regions. The performance of two deep convolutional neural networks (VGG19 and ResNet50) is investigated in this study and VGG19 reported an accuracy of 98.1%.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Sanjai P., Talal Bonny, Nida Nasir, Mohammad AlShabi, Ahmed Al Shammaa, "Marine debris detection using visual geometry group 19 and residual network 50," Proc. SPIE 12543, Ocean Sensing and Monitoring XV, 125430S (12 June 2023); https://doi.org/10.1117/12.2664012