Assessing rotational invariance of graph convolution neural networks for computer vision
This project aims to assess the property of rotational invariance within graph convolution neural networks (graph CNNs) for learning on images. Standard CNNs possess the property of translational invariance due to the sliding nature of the convolution operation and rotational invariance for small an...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2018
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| Online Access: | http://hdl.handle.net/10356/74246 |