Pulsar Candidate Classification Using A Computer Vision Method Combining with Convolution and Attention

نویسندگان

چکیده

Abstract Artificial intelligence methods are indispensable to identifying pulsars from large amounts of candidates. We develop a new pulsar identification system that utilizes the CoAtNet score two-dimensional features candidates, implements multilayer perceptron one-dimensional features, and relies on logistic regression judge corresponding scores. In data preprocessing stage, we perform two feature fusions separately, one for other which used as inputs respectively. The newly developed achieves 98.77% recall, 1.07% false positive rate (FPR) 98.85% accuracy in our GPPS test set.

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ژورنال

عنوان ژورنال: Research in Astronomy and Astrophysics

سال: 2023

ISSN: ['1674-4527', '2397-6209']

DOI: https://doi.org/10.1088/1674-4527/accdc2