Search Results for author:
Found 4 papers, 2 papers with code
Sheet Music Transformer: End-To-End Optical Music Recognition Beyond Monophonic Transcription
State-of-the-art end-to-end Optical Music Recognition (OMR) has, to date, primarily been carried out using monophonic transcription techniques to handle complex score layouts, such as polyphony, often by resorting to simplifications or specific adaptations.
Image Transformation Sequence Retrieval with General Reinforcement Learning
In this work, the novel Image Transformation Sequence Retrieval (ITSR) task is presented, in which a model must retrieve the sequence of transformations between two given images that act as source and target, respectively.
Model-based Reinforcement Learning
reinforcement-learning
+1
End-to-End Page-Level Assessment of Handwritten Text Recognition
The evaluation of Handwritten Text Recognition (HTR) systems has traditionally used metrics based on the edit distance between HTR and ground truth (GT) transcripts, at both the character and word levels.
Region-based Layout Analysis of Music Score Images
The Layout Analysis (LA) stage is of vital importance to the correct performance of an Optical Music Recognition (OMR) system.
