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The Herbarium Challenge 2019 Dataset

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arxiv 1906.05372 v2 pith:JCCGTCE7 submitted 2019-06-12 cs.CV eess.IV

The Herbarium Challenge 2019 Dataset

Kiat Chuan Tan , Yulong Liu , Barbara Ambrose , Melissa Tulig , Serge Belongie This is my paper
classification cs.CV eess.IV
keywords herbariumspecimensexpertsautomatedbotanicalchallengedatasetidentify
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Herbarium sheets are invaluable for botanical research, and considerable time and effort is spent by experts to label and identify specimens on them. In view of recent advances in computer vision and deep learning, developing an automated approach to help experts identify specimens could significantly accelerate research in this area. Whereas most existing botanical datasets comprise photos of specimens in the wild, herbarium sheets exhibit dried specimens, which poses new challenges. We present a challenge dataset of herbarium sheet images labeled by experts, with the intent of facilitating the development of automated identification techniques for this challenging scenario.

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