8 citations · 14 across the 4 of their papers we have counts for
6 papers
Over-Parameterization and Generalization in Audio Classification
Khaled Koutini, Hamid Eghbal-zadeh, Florian Henkel +2
Convolutional Neural Networks (CNNs) have been dominating classification tasks in various domains, such as machine vision, machine listening, and natural language processing. In ma…
Multi-modal Conditional Bounding Box Regression for Music Score Following
Florian Henkel, Gerhard Widmer
This paper addresses the problem of sheet-image-based on-line audio-to-score alignment also known as score following. Drawing inspiration from object detection, a conditional neura…
Low-Complexity Models for Acoustic Scene Classification Based on Receptive Field Regularization and Frequency Damping
Khaled Koutini, Florian Henkel, Hamid Eghbal-zadeh +1
Deep Neural Networks are known to be very demanding in terms of computing and memory requirements. Due to the ever increasing use of embedded systems and mobile devices with a limi…
Learning to Read and Follow Music in Complete Score Sheet Images
Florian Henkel, Rainer Kelz, Gerhard Widmer
This paper addresses the task of score following in sheet music given as unprocessed images. While existing work either relies on OMR software to obtain a computer-readable score r…
Audio-Conditioned U-Net for Position Estimation in Full Sheet Images
Florian Henkel, Rainer Kelz, Gerhard Widmer
The goal of score following is to track a musical performance, usually in the form of audio, in a corresponding score representation. Established methods mainly rely on computer-re…
Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game
Matthias Dorfer, Florian Henkel, Gerhard Widmer
Score following is the process of tracking a musical performance (audio) with respect to a known symbolic representation (a score). We start this paper by formulating score followi…