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DeepScores and Deep Watershed Detection: current state and open issues
[article]
2018
arXiv
pre-print
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This paper gives an overview of our current Optical Music Recognition (OMR) research. We recently released the OMR dataset DeepScores as well as the object detection method Deep Watershed Detector. ...
Here we summarize current and future efforts, aimed at improving usefulness on real-world task and tackling extreme class imbalance. ...
FURTHER RESEARCH ON DEEP WATERSHED DETECTION A. Augmenting inputs DeepScores, unlike many academic datasets, is extremely unbalanced. ...
arXiv:1810.05423v1
fatcat:dfnxvmyfpfb2vnafmldunajf6m
DeepScores and Deep Watershed Detection : current state and open issues
2018
Preserved Fulltext
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This paper gives an overview of our current Optical Music Recognition (OMR) research. We recently released the OMR dataset DeepScores as well as the object detection method Deep Watershed Detector. ...
Here we summarize current and future efforts, aimed at improving usefulness on real-world task and tackling extreme class imbalance. ...
FURTHER RESEARCH ON DEEP WATERSHED DETECTION
A. Augmenting inputs DeepScores, unlike many academic datasets, is extremely unbalanced. ...
doi:10.21256/zhaw-4777
fatcat:gnb7bkzu2vcjnnnx3bygtbfyby
A Baseline for General Music Object Detection with Deep Learning
2018
Applied Sciences
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However, so far, each such proposal has been based on a specific dataset and different evaluation criteria, which made it difficult to quantify the new deep learning-based state-of-the-art and assess the ...
In this paper, a baseline for general detection of musical symbols with deep learning is presented. ...
The Deep Watershed Detector proposed by Tuggener et al. ...
doi:10.3390/app8091488
fatcat:cz2vz6z6bbfmthdwwdry53t57m
Deep Watershed Detector for Music Object Recognition
[article]
2018
arXiv
pre-print
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In this paper, we introduce a novel object detection method, based on synthetic energy maps and the watershed transform, called Deep Watershed Detector (DWD). ...
We present state-of-the-art detection results of common music symbols and show DWD's ability to work with synthetic scores equally well as on handwritten music. ...
DEEP WATERSHED DETECTION In this section we present the Deep Watershed Detector (DWD) as a novel object detection system, built on the idea of the deep watershed transform [1] . ...
arXiv:1805.10548v1
fatcat:n47wyiai2zdnxc2pvg5g7pwskq
Exploiting Contextual Information with Deep Neural Networks
[article]
2020
arXiv
pre-print
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In the DeepScore project, where the usage of context is very important for the recognition of many tiny objects, we show that by carefully crafting convolutional architectures, we can achieve state-of-the-art ...
Nevertheless, there has not been much research in exploiting contextual information in deep neural networks. ...
and Deep Watershed Detection: current state and open issues [35] ; in in The International Workshop on Reading Music Systems (WoRMS 2018) (ISMIR affiliated). ...
arXiv:2006.11706v2
fatcat:bzaghxubbzcftdsvv4ogk3tfxe
Deep Learning in the Wild
[article]
2018
arXiv
pre-print
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Specifically, we give insight into deep learning projects on face matching, print media monitoring, industrial quality control, music scanning, strategy game playing, and automated machine learning, thereby ...
providing best practices for deep learning in practice. ...
Acknowledgements We are grateful for the invitation by the ANNPR chairs and the support of our business partners in Innosuisse grants 17719.1 "PANOPTES", 17963.1 "DeepScore", 25256.1 "Libra", 25335.1 " ...
arXiv:1807.04950v1
fatcat:6cb63xget5fynmjxrhzcpirvii
Deep Learning in the Wild
[chapter]
2018
Lecture Notes in Computer Science
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Specifically, we give insight into deep learning projects on face matching, print media monitoring, industrial quality control, music scanning, strategy game playing, and automated machine learning, thereby ...
providing best practices for deep learning in practice. ...
Acknowledgements We are grateful for the invitation by the ANNPR chairs and the support of our business partners in Innosuisse grants 17719.1 "PANOPTES", 17963.1 "DeepScore", 25256.1 "Libra", 25335.1 " ...
doi:10.1007/978-3-319-99978-4_2
fatcat:gmpuuzlio5ea3ck75fekk3ab7y
State-of-the-Art Model for Music Object Recognition with Deep Learning
2019
Applied Sciences
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Therefore, note recognition is the core and key aspect of music score recognition. This paper proposes an end-to-end detection model based on a deep convolutional neural network and feature fusion. ...
Music object detection is a key part of the OMR pipeline. Notes are used to record pitch and duration and have semantic information. ...
The experiment was aimed at the MUSCIMA++ dataset, showing the detection results of symbols in terms of f-scores. Tuggener et al. [20] proposed the Deep Watershed Detector. ...
doi:10.3390/app9132645
fatcat:5tox5xudojbgta7qjc67j6eswm
Optical Music Recognition: State of the Art and Major Challenges
[article]
2020
arXiv
pre-print
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This paper provides recommendations for future work, addressing some of the highlighted issues and represents a position in furthering this important field of research. ...
Recently, there has been a shift in OMR from using conventional computer vision techniques towards a deep learning approach. ...
Acknowledgments The authors acknowledge the support of the AI and Music CDT, funded by UKRI and EPSRC under grant agreement no. ...
arXiv:2006.07885v2
fatcat:pfyxmeot6fc6vemd7q3dpeq3we
The DeepScoresV2 dataset and benchmark for music object detection
2020
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Additionally, we release two state-of-the-art baselines for DeepScoresV2 based on Faster R-CNN and the Deep Watershed Detector. ...
for detection algorithms that naturally incorporate object angles. ...
Acknowledgment The authors are grateful for the support through Innosuisse grant No. 34301.1 IP-ICT "RealScore", European Research Council Advanced Grant 742870, and the continued fruitful collaboration ...
doi:10.21256/zhaw-20647
fatcat:noaqr7gaz5bjbmenjspyqpqq34
Optical Music Recognition: State of the Art and Major Challenges
2020
Zenodo
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This paper provides recommendations for future work, addressing some of the highlighted issues and represents a position in furthering this important field of research. ...
Recently, there has been a shift in OMR from using conventional computer vision techniques towards a deep learning approach. ...
Acknowledgments The authors acknowledge the support of the AI and Music CDT, funded by UKRI and EPSRC under grant agreement no. ...
doi:10.5281/zenodo.4105964
fatcat:h7yjq45ijva4pmwtptdiqbcxmi
Deep watershed detector for music object recognition
2018
Preserved Fulltext
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In this paper, we introduce a novel object detection method, based on synthetic energy maps and the watershed transform, called Deep Watershed Detector (DWD). ...
We present state-of-the-art detection results of common music symbols and show DWD's ability to work with synthetic scores equally well as on handwritten music. ...
Acknowledgements This work is financially supported by CTI grant 17963.1 PFES-ES "DeepScore". The authors are grateful for the collaboration with ScorePad AG. ...
doi:10.21256/zhaw-3760
fatcat:ovcm43mivbdvpko2qikrsvxhoq