Semantic segmentation and segmentation refinement using machine learning case study: Water turbidity segmentation

Mathematics

• Architecture 24%
• Clustering 10%
• Computer Vision 13%
• High Accuracy 11%
• Image Analysis 13%
• Image Recognition 18%
• Image Segmentation 30%
• Landsat 60%
• Learning 40%
• Machine Learning 60%
• Maximum Likelihood 9%
• Model 3%
• Object Detection 19%
• Overlapping 11%
• Pixel 26%
• Plug-in 27%
• Predict 10%
• Prediction 8%
• Refinement 48%
• Region Growing 19%
• Remote Sensing 16%
• Remote Sensing Image 21%
• Segmentation 66%
• Semantics 47%
• Software 9%
• Standards 6%
• Thresholding 13%
• Turbidity 100%
• Water 55%

Engineering & Materials Science

• Computer vision 11%
• Deep learning 49%
• Image analysis 13%
• Image recognition 15%
• Image segmentation 26%
• Machine learning 40%
• Maximum likelihood 13%
• Object detection 14%
• Pixels 20%
• Remote sensing 28%
• Semantics 37%
• Turbidity 77%
• Water 30%

Physics & Astronomy

• computer programs 4%
• computer vision 7%
• image analysis 6%
• inference 6%
• learning 26%
• machine learning 70%
• pixels 9%
• predictions 3%
• remote sensing 13%
• semantics 71%
• turbidity 72%
• water 31%