Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://doi.org/10.21256/zhaw-4255| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | DeepScores : a dataset for segmentation, detection and classification of tiny objects |
| Autor/-in: | Tuggener, Lukas Elezi, Ismail Schmidhuber, Jürgen Pelillo, Marcello Stadelmann, Thilo |
| DOI: | 10.1109/ICPR.2018.8545307 10.21256/zhaw-4255 |
| Tagungsband: | 2018 24th International Conference on Pattern Recognition (ICPR) |
| Seite(n): | 1 3704 |
| Seiten bis: | 6 3709 |
| Angaben zur Konferenz: | 24th International Conference on Pattern Recognition (ICPR 2018), Beijing, China, 20-28 August 2018 |
| Erscheinungsdatum: | 2018 |
| Verlag / Hrsg. Institution: | IEEE |
| ISBN: | 978-1-5386-3788-3 |
| Sprache: | Englisch |
| Schlagwörter: | Optical music recognition; Deep learning; Computer vision; Data set |
| Fachgebiet (DDC): | 005: Computerprogrammierung, Programme und Daten |
| Zusammenfassung: | We present the DeepScores dataset with the goal of advancing the state-of-the-art in small object recognition by placing the question of object recognition in the context of scene understanding. DeepScores contains high quality images of musical scores, partitioned into 300,000 sheets of written music that contain symbols of different shapes and sizes. With close to a hundred million small objects, this makes our dataset not only unique, but also the largest public dataset. DeepScores comes with ground truth for object classification, detection and semantic segmentation. DeepScores thus poses a relevant challenge for computer vision in general, and optical music recognition (OMR) research in particular. We present a detailed statistical analysis of the dataset, comparing it with other computer vision datasets like PASCAL VOC, SUN, SVHN, ImageNet, MS-COCO, as well as with other OMR datasets. Finally, we provide baseline performances for object classification, intuition for the inherent difficulty that DeepScores poses to state-of-the-art object detectors like YOLO or R-CNN, and give pointers to future research based on this dataset. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/6082 |
| Volltext Version: | Eingereichte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Informatik (InIT) |
| Publiziert im Rahmen des ZHAW-Projekts: | DeepScore: Digitales Notenpult mit musikalischem Verständnis durch Active Sheet Technologie |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| ICPR_2018a.pdf | 1.62 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Tuggener, L., Elezi, I., Schmidhuber, J., Pelillo, M., & Stadelmann, T. (2018). DeepScores : a dataset for segmentation, detection and classification of tiny objects [Conference paper]. 2018 24th International Conference on Pattern Recognition (ICPR), 1–3704. https://doi.org/10.1109/ICPR.2018.8545307
Tuggener, L. et al. (2018) ‘DeepScores : a dataset for segmentation, detection and classification of tiny objects’, in 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, pp. 1–3704–6–3709. Available at: https://doi.org/10.1109/ICPR.2018.8545307.
L. Tuggener, I. Elezi, J. Schmidhuber, M. Pelillo, and T. Stadelmann, “DeepScores : a dataset for segmentation, detection and classification of tiny objects,” in 2018 24th International Conference on Pattern Recognition (ICPR), 2018, pp. 1–3704–6–3709. doi: 10.1109/ICPR.2018.8545307.
TUGGENER, Lukas, Ismail ELEZI, Jürgen SCHMIDHUBER, Marcello PELILLO und Thilo STADELMANN, 2018. DeepScores : a dataset for segmentation, detection and classification of tiny objects. In: 2018 24th International Conference on Pattern Recognition (ICPR). Conference paper. IEEE. 2018. S. 1–3704–6–3709. ISBN 978-1-5386-3788-3
Tuggener, Lukas, Ismail Elezi, Jürgen Schmidhuber, Marcello Pelillo, and Thilo Stadelmann. 2018. “DeepScores : A Dataset for Segmentation, Detection and Classification of Tiny Objects.” Conference paper. In 2018 24th International Conference on Pattern Recognition (ICPR), 1–3704. IEEE. https://doi.org/10.1109/ICPR.2018.8545307.
Tuggener, Lukas, et al. “DeepScores : A Dataset for Segmentation, Detection and Classification of Tiny Objects.” 2018 24th International Conference on Pattern Recognition (ICPR), IEEE, 2018, pp. 1–3704, https://doi.org/10.1109/ICPR.2018.8545307.
Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.