LiDAR-based 3D object detection is crucial for various applications but often experiences performance degradation in real-world deployments due to domain shifts. While most studies focus on ...

Supervised Training: We train both ViT and CNN branches on labeled samples. Finding To Conquering Strategy (FTC): We find class-specific boundaries based on the fixed ViT Encoder E1 by maximizing ...

ABSTRACT: Objective: To evaluate the effects of nutritional support on treatment tolerance and complications in patients with bone tumors undergoing chemotherapy via a meta-analysis. Methods: The ...

Abstract: Recently, significant advancements have been made in 3D generative models, however training these models across diverse domains is challenging and requires an huge amount of training data ...

Abstract: Adapting generative models to specific domains presents an effective solution for satisfying specialized requirements. However, adapting to some complex domains remains challenging, ...