From Event: SPIE Defense + Commercial Sensing, 2023
Plastic pollution has emerged as one of the biggest environmentally threatening issues. Using image classification, the proposed study aids in categorizing the level of marine pollution in ocean underwater regions. This study classified the amount of pollution in the ocean using the two variants of Inception Convolutional Neural Network (CNN) models i.e., Inception- ResNet V2, and InceptionV3. High accuracies of up to 96.4% have been reported. This study will help researchers working in the field of water quality detection.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sanjai P., Talal Bonny, Nida Nasir, Mohammad AlShabi, and Ahmed Al Shammaa, "Ocean litter detection using inception transfer learning models," Proc. SPIE 12543, Ocean Sensing and Monitoring XV, 125430U (Presented at SPIE Defense + Commercial Sensing: May 04, 2023; Published: 12 June 2023); https://doi.org/10.1117/12.2664014.