Enlarging smaller images before inputting into convolutional neural network: zero-padding vs. interpolation
Abstract The input to a machine learning model is a one-dimensional feature vector. However, in recent learning models, such as convolutional and recurrent neural networks, two- and three-dimensional feature tensors can also be inputted to the model. During training, the machine adjusts its internal...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2019-11-01
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| Series: | Journal of Big Data |
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| Online Access: | http://link.springer.com/article/10.1186/s40537-019-0263-7 |