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Author

Jie Wang

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2026

EUE-Net: An Evidential Uncertainty Estimation-Based Dynamic Fusion Network for Vision–Radar Joint Gesture Recognition

Gesture recognition is essential for human-computer interaction, with visual and radar sensing technologies extensively employed in their respective fields. The complementary nature of these modalities, characterized by their feature richness, spatial-temporal resolution, and environmental robustness, has inspired rese...

Xiao-Kai Liu, Wen-Hao You, Jie Wang · 0 citations
Open access Sep 2026

Wear Prediction of Grooved Journal-Bearing Shells Using Optimized BP Neural Networks

To predict the mass loss of grooved journal-bearing shells under varying operating conditions while reducing experimental effort, accelerated wear tests were conducted on a component-level journal-bearing test rig. The effects of load, rotational speed, and oil temperature were investigated, and the worn surfaces were...

Da-Wei Li, Jian-Hui Shi, Ji-Ren Gu et al. · 0 citations
2026

Lightweight Low-Rank Spatio-Temporal Fusion for mmWave Radar-Based Aquatic Human Activity Recognition

For aquatic human activity recognition, millimeter-wave radar is less sensitive to illumination changes, visual occlusion, and privacy concerns than camera-based sensing. However, water-surface activities introduce additional challenges, including multispectrum heterogeneity, coupled temporal-motion and range/cadence s...

Lu Sun, Huan Wang, Liang-Tian Wan et al. · 0 citations
Sep 2026

Robust Decentralized Federated Learning for Automatic Modulation Classification Under Impulsive Noise and Data Heterogeneity

Automatic modulation classification (AMC) is essential for enhancing the spectral efficiency and noncooperative communication capabilities of Internet of Things (IoT) systems. IoT devices are widely deployed in untrusted intelligent scenarios where data is edge-distributed and follows a nonindependent and identically d...

Jitong Ma, Jianing Li, Tianyu Wang et al. · 0 citations
Open access Jul 2026

Visible-Infrared Person Re-Identification via Modality Disentanglement and Local Discriminative Enhancement

A disentanglement method based on Mutual Information Minimization is introduced to minimize statistical dependence between modality-shared and modality-specific features from a probability distribution perspective and a Local Discriminative Attention Module is designed to adaptively focus on highly informative body par...

Xiaokai Liu, Fangqing Zhou, Qian Song et al. · 0 citations

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