Domain Transformer

Domain transformers are neural network architectures designed to address challenges in transferring knowledge between different data domains, improving model generalization and performance in scenarios with varying data distributions. Current research focuses on applying these transformers to diverse problems, including medical image reconstruction (e.g., PET and CT scans) and heterogeneous face recognition, often incorporating them into existing models like CNNs or using them to enhance sinogram processing. This approach shows promise in improving image quality, reducing radiation exposure in medical imaging, and enabling more robust and accurate recognition across different image modalities, ultimately advancing both scientific understanding and practical applications.