2 citations · 2 across the 7 of their papers we have counts for
7 papers
SAGE: Subpopulation-Aware Generative Enhancement for Mitigating Spurious Correlations
Yiming Luo, Rongqiang Zhao, Jie Liu
Spurious correlations pose a significant challenge to the robustness of modern machine learning. The inherent imbalance in dataset distributions often leads traditional Empirical R…
Distill, Diffuse, Segment: Unsupervised 3D Semantic Segmentation for Autonomous Driving Based on Multi-Level Distillation and Graph Diffusion
Yijing Wang, Ruonan Li, Qilin Wang +2
LiDAR-based semantic segmentation is essential for autonomous-driving perception, yet dense point-wise annotations are costly, and long-tailed outdoor scenes make small safety-crit…
IGADA-IoT: IoT Sensor Energy Optimization in Wireless Sensor Networks Driven by Automatic Data Augmentation
Mingchun Sun, Rongqiang Zhao, Muhammad Abdul Munnaf +1
In wireless sensor networks (WSNs), data augmentation is a novel method to improve sampling-frequency decision performance, thereby enabling energy optimization for IoT (Internet o…
Feature Recalibration Based Olfactory-Visual Multimodal Model for Enhanced Rice Deterioration Detection
Rongqiang Zhao, Hengrui Hu, Yijing Wang +2
Multimodal methods are widely used in rice deterioration detection, but they exhibit limited capability in representing and extracting fine-grained abnormal features. Moreover, the…
IT-OSE: Exploring Optimal Sample Size for Industrial Data Augmentation
Mingchun Sun, Rongqiang Zhao, Zhennan Huang +2
In industrial scenarios, data augmentation is an effective approach to improve model performance. However, its benefits are not unidirectionally beneficial. There is no theoretical…
DS-Diffusion: Data Style-Guided Diffusion Model for Time-Series Generation
Mingchun Sun, Rongqiang Zhao, Hengrui Hu +2
Diffusion models are the mainstream approach for time series generation tasks. However, existing diffusion models for time series generation require retraining the entire framework…