Artificial intelligence (AI) and machine learning (ML) have profoundly revolutionized the aviation industry, and researchers are increasingly prioritizing these new technologies in various applications. However, the traditional end-to-end (E2E) neural networks suffer from insufficient feature extraction from single-source input data, which limits the model’s performance. To overcome this drawback, a framework of an adversarial feature fusion network (AFF-Net) is proposed and applied to the desig