IEEE

Evaluation of Encoder-Only Transformer for Multi-Step Traffic Flow Prediction

Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
IEEE

On the Dependability of Bidirectional Encoder Representations from Transformers (BERT) to Soft Errors

Abstract: Transformers are widely used in natural language processing and computer vision, and Bidirectional Encoder Representations from Transformers (BERT) is one of the most popular pre-trained ...
IEEE

DHE-Net: Dual-Encoder Hierarchical Network for Real-World Low-Cost LiDAR Point Cloud Denoising

Abstract: Light detection and ranging (LiDAR) point cloud denoising is critical for reliable environmental perception in autonomous driving and robotics. To overcome the lack of real-noise datasets ...
IEEE

MBUNeXt: Multibranch Encoder Aggregation Network Based on Layer-Fusion Strategy for Multimodal Brain Tumor Segmentation

Abstract: Multimodal brain tumor segmentation (BraTS), integrated with surgical robots and navigation systems, enables accurate surgical interventions while maximizing the preservation of surrounding ...