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Synthetic benchmarks for machine olfaction: Classification, segmentation and sensor damage

机译:机器嗅觉的综合基准:分类,分割和传感器损坏

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The design of the signal and data processing algorithms requires a validation stage and some data relevant for a validation procedure. While the practice to share public data sets and make use of them is a recent and still on-going activity in the community, the synthetic benchmarks presented here are an option for the researches, who need data for testing and comparing the algorithms under development. The collection of synthetic benchmark data sets were generated for classification, segmentation and sensor damage scenarios, each defined at 5 difficulty levels. The published data are related to the data simulation tool, which was used to create a virtual array of 1020 sensors with a default set of parameters [1].
机译:信号和数据处理算法的设计需要一个验证阶段以及一些与验证过程相关的数据。尽管共享和使用公共数据集的做法是社区中最近仍在进行的活动,但此处提供的综合基准是研究的一种选择,他们需要数据来测试和比较正在开发的算法。生成了用于分类,分割和传感器损坏情况的综合基准数据集,每个数据集定义为5个难度级别。已发布的数据与数据模拟工具有关,该工具用于创建具有默认参数集的1020个传感器的虚拟阵列[1]。

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