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Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition

Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition

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SCHALL, Martin, Dominik SACHA, Manuel STEIN, Matthias O. FRANZ, Daniel A. KEIM, 2018. Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition. Symposium on Visualization in Data Science (VDS) at IEEE VIS 2018. Berlin, Oct 22, 2018. In: Symposium on Visualization in Data Science (VDS) at IEEE VIS 2018

@inproceedings{Schall2018Visua-45050, title={Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition}, url={https://scibib.dbvis.de/publications/view/773}, year={2018}, booktitle={Symposium on Visualization in Data Science (VDS) at IEEE VIS 2018}, author={Schall, Martin and Sacha, Dominik and Stein, Manuel and Franz, Matthias O. and Keim, Daniel A.} }

<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/45050"> <dcterms:rights rdf:resource="https://kops.uni-konstanz.de/page/termsofuse"/> <dc:contributor>Franz, Matthias O.</dc:contributor> <dc:language>eng</dc:language> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-02-14T15:31:24Z</dcterms:available> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/45050/1/Schall_2-1prqtf0ga5nfs7.pdf"/> <dc:contributor>Keim, Daniel A.</dc:contributor> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/45050"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/45050/1/Schall_2-1prqtf0ga5nfs7.pdf"/> <dc:rights>terms-of-use</dc:rights> <dc:contributor>Sacha, Dominik</dc:contributor> <dc:contributor>Schall, Martin</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-02-14T15:31:24Z</dc:date> <dc:creator>Stein, Manuel</dc:creator> <dc:contributor>Stein, Manuel</dc:contributor> <dc:creator>Sacha, Dominik</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:creator>Keim, Daniel A.</dc:creator> <dc:creator>Franz, Matthias O.</dc:creator> <dcterms:abstract xml:lang="eng">Deep learning is a field of machine learning that has been the focus of active research and successful applications in recent years. Offline handwriting recognition is one of the research fields and applications were deep neural networks have shown high accuracy. Deep learning models and their training pipeline show a large amount of hyper-parameters in their data selection, transformation, network topology and training process that are sometimes interdependent. This increases the overall difficulty and time necessary for building and training a model for a specific data set and task at hand. This work proposes a novel visualization-assisted workflow that guides the model developer through the hyper-parameter search in order to identify relevant parameters and modify them in a meaningful way. This decreases the overall time necessary for building and training a model. The contributions of this work are a workflow for hyper-parameter search in offline handwriting recognition and a heat map based visualization technique for deep neural networks in multi-line offline handwriting recognition. This work applies to offline handwriting recognition, but the general workflow can possibly be adapted to other tasks as well.</dcterms:abstract> <dc:creator>Schall, Martin</dc:creator> <dcterms:title>Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition</dcterms:title> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dcterms:issued>2018</dcterms:issued> </rdf:Description> </rdf:RDF>

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