neural network - Using FCNN for multi-class semantic segmentation trained on single class labeled image data

Question

I am working on project where main task is semantic segmentation of land cover and another objects in Sentinel 2 multi-spectral images. Currently I posses dataset of 50 000 single-labeled images trimmed from Sentinel 2 tiles using OpenStreetMap polygons i.e. every image contains one class e.g. water-body. There is 7 classes in those dataset. Meant for image classification task using convolutional neural networks.

Is it possible to use those single-labeled images for training fully convolutional neural network and then use it for semantic segmentation of (larger) images containing more classes e.g. 7 ?

Or need I to create new dataset of images, each containing those 7 classes ?

Any suggestions or ideas are appreciated !

Answer 1

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