Skip to content

DALAI-project/.github

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 

Repository files navigation

DALAI - Using artificial intelligence to improve the quality and usability of digital records

The included repositories contain code and model files for tools developed as part of the the DALAI project (September 2021 - August 2023). The project was funded by the European Regional Development Fund’s ”Sustainable growth and jobs 2012–2020” programme and the City of Mikkeli.

The common aim of the different tools is to facilitate the automation of the digitisation and description of cultural heritage materials which are in the holdings of archives and other memory organisations.

Click here for more information on the included repositories
Repository Domain Content
CornerAPI Image Classification Code for an API that detects torn corners and edges from document images.
EmptyAPI Image Classification Code for an API that detects empty pages from document images.
PostitAPI Image Classification Code for an API that detects post-it/sticky notes from document images.
WritingtypeAPI Image Classification Code for an API that classifies document images based on the writing types(s) (handwritten, typewritten, combination) they contain.
FaultyImageAPI Image Classification Code for an API that combines the classification models listed above.
NER_API Named Entity Recognition Code for an API that performs named entity recognition from text input in Finnish.
Train_BERT_NER Named Entity Recognition Code for training Finnish named entity recognition (NER) model based on BERT language model.
Empty_training Image Classification Code for training a neural network model to detect empty pages from document images.
Train_document_classification Image Classification Code for training a neural network model to classify input documents into distinct classes based on the type/format of the document.
Train_fault_detection Image Classification Code for training a neural network model to detect faults like folded corners or sticky notes from document images.
Train_writing_type Image Classification Code for training a neural network model to classify document images based on the writing types(s) (handwritten, typewritten, combination) they contain.

Some of the tools are also available via Arkkiivi web user interface.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published