The OMR provided in the Collabscore project can be downloaded for research purpose. Its necessary to download : To obtain access to the complete pipeline for research purpose, please contact us at : aurelie.lemaitre@irisa.fr
KIHT project Presentation The aim of the KIHT project is to develop an intelligent learning device (« DigiPen » electronic pen) for digitized handwriting. The electronic « DigiPen » hardware is designed by STABILO with the help of the German Karlsruhe Institute of Technology (KIT). Digital devices can help pupils and teachers in the…
Description This dataset is composed of 41 children writers, acquired on Tablet. 5 recordings are dedicated to the test set, from different writers than in training. This refers to 1307 examples in training and 170 in the test set. Every recording session generates files from the data acquisition mobile app.…
Description This dataset is composed of 40 adult writers, acquired on Paper. 5 recordings are dedicated to the test set, from different writers than in training. This refers to 2983 examples in training and 281 in the test set. Every recording session generates files from the data acquisition mobile app.…
This dataset is composed of 149 recordings of adult writers, acquired on Tablet. Every recording session generates files from the data acquisition mobile app. The sensor signals file has 13 columns: milliseconds, accelerometer front (x, y, z), accelerometer rear (x, y, z), gyroscope (x, y, z), magnetometer (x, y, z),…
KIHT project Presentation The aim of the KIHT project is to develop an intelligent learning device (« DigiPen » electronic pen) for digitized handwriting. The electronic « DigiPen » hardware is designed by STABILO with the help of the German Karlsruhe Institute of Technology (KIT). Digital devices can help pupils and teachers in the…
This dataset is composed of 30 recordings of adult writers, acquired on Tablet. Every recording session generates files from the data acquisition mobile app. The sensor signals file has 13 columns: milliseconds, accelerometer front (x, y, z), accelerometer rear (x, y, z), gyroscope (x, y, z), magnetometer (x, y, z),…
Description We introduce LPR-MNIST, a synthetic dataset replicating the key aspects of syntax evolution on vehicle license plates, as explored in the paper Relaxed syntax modeling in Transformers for future-proof license plate recognition. LPR-MNIST is a collection of 100,000 synthetic image-text pairs, generated by concatenating 5 black-and-white digits from MNIST, each…
The Synthetic Text line Image Generator (STIG) is a software dedicated to handwritten textline generation. It is available for free under conditions (see below). Description The Synthetic Text line Image Generator is a Python code dedicated to the generation of synthetic handwritten textline images. The software can generate textlines looking…
The Modular Light Transformer (MLT) is a software dedicated to text recognition. It is available for free under conditions (see below). Description The Modular Light Transformer is a software dedicated to text recognition. It is based on a lightweight Transformer-based neural network dealing with text-line images. The proposed software is…