remove dead

Author: robmarkcole

README.md

@@ -3587,7 +3587,7 @@ Image quality describes the degree of accuracy with which an image can represent
 
 Training data can be hard to acquire, particularly for rare events such as change detection after disasters, or imagery of rare classes of objects. In these situations, generating synthetic training data might be the only option. This has become quite sophisticated, with 3D models being use with open source games engines such as [Unreal](https://www.unrealengine.com/en-US/).
 
-- [The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation](https://arxiv.org/ftp/arxiv/papers/2001/2001.05130.pdf) with [repo](https://github.com/timqqt/Synthinel)
+- [The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation](https://github.com/timqqt/Synthinel)
 
 - [RarePlanes](https://registry.opendata.aws/rareplanes/) -> incorporates both real and synthetically generated satellite imagery including aircraft. Read the [arxiv paper](https://arxiv.org/abs/2006.02963) and checkout [this repo](https://github.com/jdc08161063/RarePlanes). Note the dataset is available through the AWS Open-Data Program for free download