1000种西欧植物，超10万张图像，用众包数据评测大规模识别系统。
LifeCLEF Plant Identification Task 2015
- 基于十万级图像和千种植物的众包数据集，模拟真实生物多样性监测场景。
- 参赛团队采用多种方法，整体识别准确率在千类物种上达到一定水平。
- 适合关注生态监测、众包数据应用与植物识别的实际落地研究者。
LifeCLEF植物识别挑战赛旨在评估大规模植物识别方法与系统的性能，接近真实世界生物多样性监测的实际条件。2015年评估基于超过10万张图像构成的数据集，涵盖西欧1000种植物。该数据集源自自2011年起启动的大型公众参与感知平台，目前已吸引数万名参与者。本文详细介绍了挑战赛的资源与评估流程，总结了各参赛团队所采用的方法与系统，并对主要成果进行了分析。
原文摘要 · Abstract (English)
The LifeCLEF plant identification challenge aims at evaluating plant identification methods and systems at a very large scale, close to the conditions of a real-world biodiversity monitoring scenario. The 2015 evaluation was actually conducted on a set of more than 100K images illustrating 1000 plant species living in West Europe. The main originality of this dataset is that it was built through a large-scale participatory sensing plateform initiated in 2011 and which now involves tens of thousands of contributors. This overview presents more precisely the resources and assessments of the challenge, summarizes the approaches and systems employed by the participating research groups, and provides an analysis of the main outcomes.
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