VGG Cell Dataset from Learning To Count Objects in Images
Lempitsky, V. and Zisserman, A.

cells.zip 16.34MB
Type: Dataset
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Metadata:
@article{,
title= {VGG Cell Dataset from Learning To Count Objects in Images  },
keywords= {},
journal= {},
author= {Lempitsky, V. and Zisserman, A.},
booktitle= {Advances in Neural Information Processing Systems},
year= {2010},
url= {http://www.robots.ox.ac.uk/~vgg/research/counting/index_org.html},
license= {},
abstract= {![](https://i.imgur.com/ydlsPEh.png)

We generated a dataset of  200 images, and used random subsets of the first 100 images to perform training and parameter validations, and the second 100 images to test the counting accuracy. Below, we show some representative results for cell counting for the previously unseen images 



### Acknowledgements

This work is a part of the EU VisRec project (ERC grant VisRec no. 228180). },
superseded= {},
terms= {}
}

Citation:
Lempitsky, V. & Zisserman, A.. (2010). VGG Cell Dataset from Learning To Count Objects in Images [Data set]. Academic Torrents. https://academictorrents.com/details/b32305598175bb8e03c5f350e962d772a910641c
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