7 citations · 9 across the 9 of their papers we have counts for
9 papers
Semantic Sampling via Learnable Observation Front Ends
Yuxuan Liu, Guangming Shi, Pengfei He +2
Sampling determines the form of information available to downstream reconstruction systems. Conventional lowrate sampling forms finite-dimensional observations directly from the ra…
SPAT: A Semantic Port-Aware Adaptive-Rate Transmission Protocol for Semantic Communication
Yunhao Wang, Shuai Ma, Bin Shen +4
With the evolution of 6G, semantic communication has emerged as a promising paradigm by prioritizing the delivery of task-relevant meaning over strict bit-level correctness. Howeve…
NOC4SC: A Bandwidth-Efficient Multi-User Semantic Communication Framework for Interference-Resilient Transmission
Yunhao Wang, Shuai Ma, Pengfei He +3
With the explosive growth of connected devices and emerging applications, current wireless networks are encountering unprecedented demands for massive user access, where the inter-…
SITP: A High-Reliability Semantic Information Transport Protocol Without Retransmission for Semantic Communication
Yunhao Wang, Shuai Ma, Youlong Wu +4
With the evolution of 6G networks, modern communication systems are facing unprecedented demands for high reliability and low latency. However, conventional transport protocols are…
Feature Partitioning and Semantic Equalization for Intrinsic Robustness in Semantic Communication under Packet Loss
Xiao Yang, Shuai Ma, Yong Liang +1
Semantic communication can improve transmission efficiency by focusing on task-relevant information. However, under packet-based communication protocols, any error typically result…
Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining
Jiarun Liu, Hao Yang, Hong-Yu Zhou +8
Accurate medical image segmentation demands the integration of multi-scale information, spanning from local features to global dependencies. However, it is challenging for existing…
Enhancing Representation in Medical Vision-Language Foundation Models via Multi-Scale Information Extraction Techniques
Weijian Huang, Cheng Li, Hong-Yu Zhou +6
The development of medical vision-language foundation models has attracted significant attention in the field of medicine and healthcare due to their promising prospect in various…
MLIP: Medical Language-Image Pre-training with Masked Local Representation Learning
Jiarun Liu, Hong-Yu Zhou, Cheng Li +4
Existing contrastive language-image pre-training aims to learn a joint representation by matching abundant image-text pairs. However, the number of image-text pairs in medical data…
Multimodal self-supervised learning for lesion localization
Hao Yang, Hong-Yu Zhou, Cheng Li +7
Multimodal deep learning utilizing imaging and diagnostic reports has made impressive progress in the field of medical imaging diagnostics, demonstrating a particularly strong capa…