Using Convolutional Neural Networks to Develop State-of-the-Art Flotation Froth Image Sensors
Convolutional neural networks provide a state-of-the-art approach to the development of froth image sensors. In this study, it is shown that a pretrained neural network architecture, namely VGG16, can be used to obtain significant improvements in froth image sensors. However, training of these netwo...
| Main Authors: | , |
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| Format: | Journal Article |
| Published: |
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/73068 |