Images Classification Recipe

Images Classification

Convolutional Neural Networks (CNN) and Transfer Learning for Heritage Images Classification

This recipe exposes an image classification scenario, aiming to deduce the technique or genre of images (picture, drawing, map...) using a Convolutional Neural Networks trained model (supervised approach with transfer learning).

This recipe may have various library use cases, particularly for cataloguing and information retrieval systems.

This recipe is based on BnF materials

Goals

This recipes includes a basic introduction to neural networks and deep learning (formal neuron model, neural networks and convolutional neural networks) and a hands-on session:

• creation of a training dataset
• training of a classification model with commercial APIs or open source IA frameworks
• application of the model to the heritage images to be classified

Educational resources

The material we are offering to realize the recipe.

Introduction to the core technology used

the basic theory

Implementation notes

• prose description
• resources and skills needed
• the technical information needed to complete a sub-task of the recipe, or the whole recipe (Jupyter notebooks, detailed Git readme...)
• training datasets used ...

Other resources

Other resources related to this recipe:

• Scientific material: white papers, papers, conference presentation, etc.
• Technical material: user guide for the tools, language, scripts, formats used...
• Training/learning material: blogs, MOOC, books, tutorial...

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