Object detection and extraction from fixed-layout documents using Deep Learning

  • project:
  • client:
  • year: 2018
  • website:

challenge:

Technical or scientific documents usually have a lot of figures, tables or diagrams besides text. In one of our systems it was crucial to extract these kind of objects from a PDF document as a separate image and take note of its location in the original document.

tools used:

Keras
Tensorflow
Python
CNN
Flask
We have used deep learning techniques to identify objects of interest in the documents.

solution:

We have implemented the YOLO detection algorithm and evaluated multiple architectures of the underlying convolutional neural network.

We have pretrained the model on a large set of labeled images and then applied transfer learning to our specific task.

To increase the data set for our specific task, we have applied data augmentation.

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impact:

Using Deep Learning mechanism we created system which can detect and extract objects from fixed-layout documents.