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DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
Document Image and Voice Analysis Group (DIVA), University of Fribourg, Switzerland.
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2018 (English)In: Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR 2018, IEEE, 2018, p. 423-428, article id 8583798Conference paper, Published paper (Refereed)
Abstract [en]

We introduce DeepDIVA: an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing scientific results can be a frustrating experience, not only in document image analysis but in machine learning in general. Using DeepDIVA a researcher can either reproduce a given experiment or share their own experiments with others. Moreover, the framework offers a large range of functions, such as boilerplate code, keeping track of experiments, hyper-parameter optimization, and visualization of data and results. To demonstrate the effectiveness of this framework, this paper presents case studies in the area of handwritten document analysis where researchers benefit from the integrated functionality. DeepDIVA is implemented in Python and uses the deep learning framework PyTorch. It is completely open source(1), and accessible as Web Service through DIVAServices(2).

Place, publisher, year, edition, pages
IEEE, 2018. p. 423-428, article id 8583798
Series
International Conference on Handwriting Recognition, ISSN 2167-6445
Keywords [en]
Framework, Open-Source, Deep Learning, Neural Networks, Reproducible Research, Machine Learning, Hyper-parameters Optimization, Python
National Category
Computer Sciences
Research subject
Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-73160DOI: 10.1109/ICFHR-2018.2018.00080ISI: 000454983200071Scopus ID: 2-s2.0-85052223452ISBN: 978-1-5386-5875-8 (print)OAI: oai:DiVA.org:ltu-73160DiVA, id: diva2:1295313
Conference
16th International Conference on Frontiers in Handwriting Recognition, ICFHR 2018, 5- August 2018, Niagara Fall, United States
Available from: 2019-03-11 Created: 2019-03-11 Last updated: 2019-09-13Bibliographically approved

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Liwicki, Marcus

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  • apa
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Output format
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