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rcnn-model

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Mask R-CNN creates a high-quality segmentation mask in addition to the Faster R-CNN network. In addition to class labels and scores, a segmentation mask is created for the objects detected by this neural network. In this repository, using Anaconda prompt step by step Mask R-CNN setup is shown.

  • Updated Aug 9, 2022
  • Jupyter Notebook

This project is centered around leveraging CRNN (Convolution Recurrent Neural Networks) and Digital Image Processing principles to extract license plates from car images and convert them to text. By using advanced AI algorithms and computer vision techniques, the project aims to provide a reliable and accurate way to recognize license plates.

  • Updated Dec 12, 2022
  • Python
AREnets

Tensorflow-based framework which lists attentive implementation of the conventional neural network models (CNN, RNN-based), applicable for Relation Extraction classification tasks as well as API for custom model implementation

  • Updated Nov 8, 2023
  • Python

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