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LifeCLEF 2016: Multimedia Life Species Identification Challenges

机译:LifeCLEF 2016:多媒体生命物种识别挑战

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Using multimedia identification tools is considered as one of the most promising solutions to help bridge the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g., iSpot, Xeno-canto, Tela Botanica, etc.) as well as big monitoring equipment have actually started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art analysis techniques on such data is still not well understood and is far from reaching real world requirements. The LifeCLEF lab proposes to evaluate these challenges around 3 tasks related to multimedia information retrieval and fine-grained classification problems in 3 domains. Each task is based on large volumes of real-world data and the measured challenges are defined in collaboration with biologists and environmental stakeholders to reflect realistic usage scenarios. For each task, we report the methodology, the data sets as well as the results and the main outcomes.
机译:使用多媒体识别工具被认为是最有希望的解决方案之一,可帮助弥合分类学鸿沟,并建立有关身份,地理分布和生物物种进化的准确知识。大型,结构化的自然观察者社区(例如iSpot,Xeno-canto,Tela Botanica等)以及大型监测设备实际上已经开始产生出色的多媒体记录。不幸的是,对此类数据的最新分析技术的性能仍未得到很好的理解,还远远达不到现实世界的要求。 LifeCLEF实验室建议围绕与3个领域的多媒体信息检索和细分类问题相关的3个任务评估这些挑战。每个任务都基于大量的现实世界数据,并且与生物学家和环境利益相关者合作定义了测得的挑战,以反映实际的使用场景。对于每个任务,我们报告方法,数据集以及结果和主要结果。

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