000276445 001__ 276445
000276445 005__ 20210129220903.0
000276445 0247_ $$2doi$$a10.1016/j.patrec.2015.10.013
000276445 0247_ $$2ISSN$$a0167-8655
000276445 0247_ $$2ISSN$$a1872-7344
000276445 0247_ $$2WOS$$aWOS:000383822500011
000276445 0247_ $$2altmetric$$aaltmetric:4770297
000276445 037__ $$aFZJ-2015-06884
000276445 041__ $$aEnglish
000276445 082__ $$a004
000276445 1001_ $$0P:(DE-HGF)0$$aMinervini, Massimo$$b0$$eCorresponding author
000276445 245__ $$aFinely-grained annotated datasets for image-based plant phenotyping
000276445 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2015
000276445 3367_ $$2DRIVER$$aarticle
000276445 3367_ $$2DataCite$$aOutput Types/Journal article
000276445 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1485963229_20950
000276445 3367_ $$2BibTeX$$aARTICLE
000276445 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000276445 3367_ $$00$$2EndNote$$aJournal Article
000276445 520__ $$aImage-based approaches to plant phenotyping are gaining momentum providing fertile ground for several interesting vision tasks where fine-grained categorization is necessary, such as leaf segmentation among a variety of cultivars, and cultivar (or mutant) identification. However, benchmark data focusing on typical imaging situations and vision tasks are still lacking, making it difficult to compare existing methodologies. This paper describes a collection of benchmark datasets of raw and annotated top-view color images of rosette plants. We briefly describe plant material, imaging setup and procedures for different experiments: one with various cultivars of Arabidopsis and one with tobacco undergoing different treatments. We proceed to define a set of computer vision and classification tasks and provide accompanying datasets and annotations based on our raw data. We describe the annotation process performed by experts and discuss appropriate evaluation criteria. We also offer exemplary use cases and results on some tasks obtained with parts of these data. We hope with the release of this rigorous dataset collection to invigorate the development of algorithms in the context of plant phenotyping but also provide new interesting datasets for the general computer vision community to experiment on. Data are publicly available at http://www.plant-phenotyping.org/datasets.
000276445 536__ $$0G:(DE-HGF)POF3-582$$a582 - Plant Science (POF3-582)$$cPOF3-582$$fPOF III$$x0
000276445 536__ $$0G:(DE-HGF)POF3-583$$a583 - Innovative Synergisms (POF3-583)$$cPOF3-583$$fPOF III$$x1
000276445 588__ $$aDataset connected to CrossRef
000276445 7001_ $$0P:(DE-Juel1)129315$$aFischbach, Andreas$$b1$$ufzj
000276445 7001_ $$0P:(DE-Juel1)129394$$aScharr, Hanno$$b2$$ufzj
000276445 7001_ $$0P:(DE-HGF)0$$aTsaftaris, Sotirios A.$$b3
000276445 773__ $$0PERI:(DE-600)1466342-9$$a10.1016/j.patrec.2015.10.013$$gp. S0167865515003645$$p80–89$$tPattern recognition letters$$v81$$x0167-8655$$y2015
000276445 8564_ $$uhttp://www.sciencedirect.com/science/article/pii/S0167865515003645
000276445 8564_ $$uhttps://juser.fz-juelich.de/record/276445/files/1-s2.0-S0167865515003645-main.pdf$$yRestricted
000276445 8564_ $$uhttps://juser.fz-juelich.de/record/276445/files/1-s2.0-S0167865515003645-main.gif?subformat=icon$$xicon$$yRestricted
000276445 8564_ $$uhttps://juser.fz-juelich.de/record/276445/files/1-s2.0-S0167865515003645-main.jpg?subformat=icon-1440$$xicon-1440$$yRestricted
000276445 8564_ $$uhttps://juser.fz-juelich.de/record/276445/files/1-s2.0-S0167865515003645-main.jpg?subformat=icon-180$$xicon-180$$yRestricted
000276445 8564_ $$uhttps://juser.fz-juelich.de/record/276445/files/1-s2.0-S0167865515003645-main.jpg?subformat=icon-640$$xicon-640$$yRestricted
000276445 8564_ $$uhttps://juser.fz-juelich.de/record/276445/files/1-s2.0-S0167865515003645-main.pdf?subformat=pdfa$$xpdfa$$yRestricted
000276445 909CO $$ooai:juser.fz-juelich.de:276445$$pVDB
000276445 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129315$$aForschungszentrum Jülich GmbH$$b1$$kFZJ
000276445 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129394$$aForschungszentrum Jülich GmbH$$b2$$kFZJ
000276445 9131_ $$0G:(DE-HGF)POF3-582$$1G:(DE-HGF)POF3-580$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lKey Technologies for the Bioeconomy$$vPlant Science$$x0
000276445 9131_ $$0G:(DE-HGF)POF3-583$$1G:(DE-HGF)POF3-580$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lKey Technologies for the Bioeconomy$$vInnovative Synergisms$$x1
000276445 9141_ $$y2015
000276445 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000276445 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology
000276445 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bPATTERN RECOGN LETT : 2014
000276445 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000276445 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000276445 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000276445 915__ $$0StatID:(DE-HGF)0550$$2StatID$$aNo Authors Fulltext
000276445 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000276445 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz
000276445 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000276445 9201_ $$0I:(DE-Juel1)IBG-2-20101118$$kIBG-2$$lPflanzenwissenschaften$$x0
000276445 980__ $$ajournal
000276445 980__ $$aVDB
000276445 980__ $$aI:(DE-Juel1)IBG-2-20101118
000276445 980__ $$aUNRESTRICTED