Body: <p>I am trying to learn more about text-independent writer identification and was hoping for some advice.</p>
  <p>I have a folder with 100k images, each of them with a different handwritten sentence. All of the images have sentences of different lengths. They range from about 30 to 80 English characters. The file names start at <code>1.png</code> and go up to <code>100k.png</code>. That's it, as far as input data. 95% of the sentences are written by different writers. 5% are written by the same writers. Some writers might have written 2 sentences, while others 300+.</p>
  <p>Does anyone know of an identification method that would be able to determine what images were written by the same writer?</p>
  <p>I know that most methods require each writer to have provided a full page of sample writing for training, but, of course, I do not have that.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-07-13T20:02:08.483Z
Comments.Text: I have edited your post to clarify it. Make sure that I did not change the meaning of your sentences.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-07-15T21:09:49.113Z
Comments.Text: Is the data labeled, i.e. do you know which sentence has been produced by which writer? If so, I'd start out training a Recurrent Neural Network, which is specialized on working with sequence data.
Comments.UserDisplayName: Daniel B.
Tags: <machine-learning><convolutional-neural-networks><ai-design><natural-language-understanding>
Title: Can text-independent writer identification be done without multi-sentence training datasets for each writer?
UserDisplayName: user38553
ThreadText: # Can text-independent writer identification be done without multi-sentence training datasets for each writer?
  
  (Asked by: username_0 on 2020-07-11)
  
  I am trying to learn more about text-independent writer identification and was hoping for some advice.
  
  I have a folder with 100k images, each of them with a different handwritten sentence. All of the images have sentences of different lengths. They range from about 30 to 80 English characters. The file names start at `1.png` and go up to `100k.png`. That's it, as far as input data. 95% of the sentences are written by different writers. 5% are written by the same writers. Some writers might have written 2 sentences, while others 300+.
  
  Does anyone know of an identification method that would be able to determine what images were written by the same writer?
  
  I know that most methods require each writer to have provided a full page of sample writing for training, but, of course, I do not have that.
  
  **Tags:** machine-learning, convolutional-neural-networks, ai-design, natural-language-understanding
  
  > **Comments:**
  > **username_1**: I have edited your post to clarify it. Make sure that I did not change the meaning of your sentences.  
  > **username_2**: Is the data labeled, i.e. do you know which sentence has been produced by which writer? If so, I'd start out training a Recurrent Neural Network, which is specialized on working with sequence data.  
  
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  ## 0 answers
  
  