Ziyatdinov Andrey, Perera Alexandre
B2SLab, Department of ESAII, Universitat Politenica de Catalunya, Pau Gargallo 5, Barcelona, Spain ; Centro de Investigacion Biomedica en Red en Bioingenierıa, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain.
Data Brief. 2015 Feb 27;3:126-30. doi: 10.1016/j.dib.2015.02.011. eCollection 2015 Jun.
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].
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程序相关的数据。虽然共享公共数据集并加以利用的做法在该领域是一项近期且仍在进行的活动，但此处呈现的合成基准是那些需要数据来测试和比较正在开发的算法的研究人员的一种选择。合成基准数据集的收集是针对分类、分割和传感器损坏场景生成的，每个场景都定义了5个难度级别。已发布的数据与数据模拟工具相关，该工具用于使用一组默认参数创建一个包含1020个传感器的虚拟阵列[1]。
