Application of AI Technology in Pulsar Candidate Identification

As artificial intelligence (AI) technology has continued to develop, its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes, and it has been widely applied across various fields. In the field of astronomy, AI techniques have demonstrated unique advantages, particularly in the identification of pulsars and their candidates. AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency. This paper systematically surveys commonly used AI models for pulsar candidate identification, analyzing and discussing the typical applications of machine learning, artificial neural networks, convolutional neural networks, and generative adversarial networks in candidate identification. Furthermore, it explores how the introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing, thus playing a significant role in advancing pulsar research and the field of astronomy.