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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.
Vise andre og tillknytning
2018 (engelsk)Inngår i: Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR 2018, IEEE, 2018, s. 423-428, artikkel-id 8583798Konferansepaper, Publicerat paper (Fagfellevurdert)
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).

sted, utgiver, år, opplag, sider
IEEE, 2018. s. 423-428, artikkel-id 8583798
Serie
International Conference on Handwriting Recognition, ISSN 2167-6445
Emneord [en]
Framework, Open-Source, Deep Learning, Neural Networks, Reproducible Research, Machine Learning, Hyper-parameters Optimization, Python
HSV kategori
Forskningsprogram
Maskininlärning
Identifikatorer
URN: urn:nbn:se:ltu:diva-73160DOI: 10.1109/ICFHR-2018.2018.00080ISI: 000454983200071Scopus ID: 2-s2.0-85052223452ISBN: 978-1-5386-5875-8 (tryckt)OAI: oai:DiVA.org:ltu-73160DiVA, id: diva2:1295313
Konferanse
16th International Conference on Frontiers in Handwriting Recognition, ICFHR 2018, 5- August 2018, Niagara Fall, United States
Tilgjengelig fra: 2019-03-11 Laget: 2019-03-11 Sist oppdatert: 2019-09-13bibliografisk kontrollert

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