OCR and Layout Analysis Quiz

What you'll be asked

1. What is the primary purpose of Optical Character Recognition (OCR) in document processing?
2. During document layout analysis, why is it important to perform 'Region of Interest' (ROI) segmentation before applying OCR?
3. In the context of processing invoices, what does 'Table Extraction' typically involve?
4. Which preprocessing technique is most effective for improving OCR accuracy on a document with heavy 'salt-and-pepper' noise or scanning artifacts?
5. When implementing a deep learning-based Layout Analysis model, why might you choose a model using 'Graph Neural Networks' (GNNs) over a standard 'Convolutional Neural Network' (CNN)?

Answers and explanations come after you submit.