Image-based table cell detection: a new dataset and an improved detection method.

Table detection has been an interesting and challenging problem in the field of document analyses. Object detection algorithms such as Faster-RCNN has been exploited so many times to detect tables in the documents. This is just another experiment but with a different architecture which is Mask_RCNN.

deeplabv3plus (Google's new algorithm for semantic segmentation) in keras：Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Using deep-leaning detect tables in the documet image

Table Detection using Deep Learning FasterRCNN

SegNet + CRF as RNN

Code for 'PolarMask: Single Shot Instance Segmentation with Polar Representation'

Graphical Object Detection in Document Images

Convolutional LSTM for video segmentation with Keras

tableGAN is a synthetic data generation technique (Data Synthesis based on Generative Adversarial Networks paper) based on Generative Adversarial Network architecture (DCGAN).

This repository contains a 403 images dataset for table detection in documents.

Table Detection From Images Using Deep Learning

Activation Maps (Layers Outputs) and Gradients in Keras.

Document Understanding tools

This project uses open-cv with tesseract to detect and extract single level table from pdfs.

PyTorch Implementations for DeeplabV3 and PSPNet

Visualization techiques for deep learning neural networks using Keras