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A neotropical Miocene pollen database employing image-based search and semantic modeling

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dc.contributor.author Han, Jing Ginger en
dc.contributor.author Cao, Hongfei en
dc.contributor.author Barb, Adrian en
dc.contributor.author Punyasena, Surangi W. en
dc.contributor.author Jaramillo, Carlos A. en
dc.contributor.author Shyu, Chi-Ren en
dc.date.accessioned 2015-02-25T18:30:23Z
dc.date.available 2015-02-25T18:30:23Z
dc.date.issued 2014
dc.identifier.citation Han, Jing Ginger, Cao, Hongfei, Barb, Adrian, Punyasena, Surangi W., Jaramillo, Carlos A., and Shyu, Chi-Ren. 2014. "<a href="https://stri-apps.si.edu/docs/publications/pdfs/Han_2014_image_pollen_search_punyasena.pdf">A neotropical Miocene pollen database employing image-based search and semantic modeling</a>." <em>Applications in Plant Sciences</em>. 2 (8):<a href="https://doi.org/10.3732/apps.1400030">https://doi.org/10.3732/apps.1400030</a> en
dc.identifier.issn 2168-0450
dc.identifier.uri http://hdl.handle.net/10088/24623
dc.description.abstract • PREMISE OF THE STUDY: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • METHODS: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • RESULTS: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • DISCUSSION: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. en
dc.relation.ispartof Applications in Plant Sciences en
dc.title A neotropical Miocene pollen database employing image-based search and semantic modeling en
dc.type Journal Article en
dc.identifier.srbnumber 127925
dc.identifier.doi 10.3732/apps.1400030
rft.jtitle Applications in Plant Sciences
rft.volume 2
rft.issue 8
dc.description.SIUnit STRI en
dc.relation.url https://stri-apps.si.edu/docs/publications/pdfs/Han_2014_image_pollen_search_punyasena.pdf


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