Weihang Liu

This page is a disambiguation page, it actually contains multiple papers from persons of the same or a similar name.

Bibliography

2026
Quantitative Error Feedback for Quantization Noise Reduction of Filtering Over Graphs.
IEEE Trans. Signal Process., 2026

FedLSC: Federated learning with layer similarity comparison for cross-institutional skin cancer image classification.
Expert Syst. Appl., 2026

2025
CoARF++: Content-Aware Radiance Field Aligning Model Complexity With Scene Intricacy.
IEEE Trans. Vis. Comput. Graph., October, 2025

Duplex-GS: Proxy-Guided Weighted Blending for Real-Time Order-Independent Gaussian Splatting.
CoRR, August, 2025

Adaptive Time-step Training for Enhancing Spike-Based Neural Radiance Fields.
CoRR, July, 2025

Hierarchical feature selection via joint local label enhancement and neighborhood label distribution correlation.
Knowl. Based Syst., 2025

CityGo: Lightweight Urban Modeling and Rendering with Proxy Buildings and Residual Gaussians.
Proceedings of the SIGGRAPH Asia 2025 Conference Papers, 2025

TSFI-Net: An Ensemble Network for Improving Skin Cancer Detection Using Transfer Learning and Fuzzy Integral.
Proceedings of the International Joint Conference on Neural Networks, 2025

2024
A Circularly Polarized Non-Resonant Slotted Waveguide Antenna Array for Wide-Angle Scanning.
Sensors, May, 2024

A Novel Flood Risk Analysis Framework Based on Earth Observation Data to Retrieve Historical Inundations and Future Scenarios.
Remote. Sens., April, 2024

Content-Aware Radiance Fields: Aligning Model Complexity with Scene Intricacy Through Learned Bitwidth Quantization.
Proceedings of the Computer Vision - ECCV 2024, 2024

2022
Improving Spatial Disaggregation of Crop Yield by Incorporating Machine Learning with Multisource Data: A Case Study of Chinese Maize Yield.
Remote. Sens., 2022

Massive MIMO Channel Prediction in Real Propagation Environments Using Tensor Decomposition and Autoregressive Models.
Proceedings of the 2022 IEEE 33rd Annual International Symposium on Personal, 2022


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