Development of deep neural network for document layout analysis over publaynet dataset -- 2

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Development of deep neural network for document layout analysis over publaynet dataset.

You have to train on the publaynet dataset and develop a model for detecting the text, title, image,

He/she has to use CNN or RNN or a combination of both or transformers to extract features from document images.

He has to use transfer learning to conduct fine tuning of model pretrained on Publaynet Dataset.

He has to compare different deep learning architectures like CNN, faster RCN, RNN, and transformer based models. He can use facebook detectron2 or Layoutparser for fine tuning

The model will be trained on Publaynet dataset and its performance will be evaluated using metrics such as accuracy, F1 score, recall and precision.

The performance of developed network can also be compared to existing annotation methods using statistical tests such as T tests and annova.

Proper graphs about the iterations has to be plotted.

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Python Informatique en Nuage Machine Learning (ML) Science des données

Nº du projet : #36654222

À propos du projet

3 propositions Projet à distance Actif il y a 3 mois

3 freelances font une offre moyenne de 43 $ pour ce travail

aqi422696

I am excited to submit this proposal for the development of a deep neural network for document layout analysis using the Publaynet dataset. This project aims to leverage state-of-the-art deep learning techniques, inclu Plus

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uhasnain

I understand that you are looking for someone to develop a deep neural network for document layout analysis over the PubLayNet dataset. You need this model to be trained on the dataset and its performance evaluated usi Plus

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souhayle

hello im souhayle , i have workded on some of these type of networks i also worked on trading models for predicting prices lately, i think i will be able to work with you on your document, contact me for more

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