The Fermi-LAT DR1 and DR2 4FGL catalogues feature more than 5000 gamma-ray sources of which about one fourth are not associated with already known objects, and approximately one third are associated with blazars of uncertain nature. We perform a three-category classification of the 4FGL DR1 and DR2 sources independently, using an ensemble of Artificial Neural Networks (ANNs) to characterize them based on the likelihood of being a Pulsar (PSR), a BL Lac type blazar (BLL) or a Flat Spectrum Radio Quasar (FSRQ). We identify candidate PSR, BLL, and FSRQ among the unassociated sources with approximate equipartition among the three categories and select 10 classification outliers as potentially interesting for follow-up studies.

中文翻译：

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4FGL源的人工神经网络分类

Fermi-LAT DR1 和 DR2 4FGL 目录包含 5000 多个伽马射线源，其中约四分之一与已知天体无关，约三分之一与性质不确定的耀变体有关。我们独立地对 4FGL DR1 和 DR2 源进行三类分类，使用人工神经网络 (ANN) 集合来根据它们是 Pulsar (PSR)、BL Lac 型耀变体 (BLL) 或平面频谱无线电类星体（FSRQ）。我们在不相关的来源中识别候选 PSR、BLL 和 FSRQ，并在三个类别之间进行近似均分，并选择 10 个分类异常值作为后续研究可能感兴趣的。