Deep Learning approach for Signature extraction from emails Deep Learning (DL) is now days are used in various fields. I may like to know any idea/approach on usin DL for Signature extraction from emails. 

There are some papers which uses ML like http://keg.cs.tsinghua.edu.cn/jietang/publications/f142-tang.pdf
http://www.cs.cmu.edu/~vitor/papers/sigFilePaper_finalversion.pdf  &nbsp;&nbsp; there are few more.

There are some open source libraries in Python like talon which uses NLP (Regular expressions and other techniques) and uses ML algorithms ( SVM ) for the same.

I have done a little research but I am not getting any resource or any idea on how to proceed with DL for this task.
I thought of using seq2seq models but I am not sure it can be of much help for this task. I am not sure whether summarization techniques can be useful.
Any idea or resources for the same can be helpful.
Detecting a signature in an email is more like a detection problem in an image rather than a natural language processing (NLP) problem. It does not particularly matter what the signature says, you simply want to be able to detect it. 

In such a case, detection in images is currently dominated by convolutional neural networks (CNN). This is a very powerful technique which has proved to be the best for a multitude of image-based tasks. However, it requires a very large dataset. So you will need to collect a lot of varied examples and annotate them yourself. 

The output of the CNN can provide either a binary output 0/1 determining if a signature exists. Or it can provide an output which is the coordinates of the center of the signature (X, Y coordinates) such that you can know where it is placed in the document.