Rencheng Song

An open-set learning framework for EEG-based sleep stage classification

Qiunan Feng, Chang Li, Hu Peng, Heyuan Qiao et autres

OBJECTIVE: Existing sleep stage classification methods are typically developed under the closed-set assumption, where all sleep categories are predefined and known, thereby neglecting the presence of unknown sleep patterns in real-world electroencephalogram (EEG) analysis. This study aims to address this limitation by …

cn (code pays fourni par la source)

A Hybrid Convolutional, Mamba and Spiking Neural Network Architecture Search for Seizure Prediction

Bo Yu, Chang Li, Rencheng Song, Xiang Liu et autres

cn (code pays fourni par la source)

Uncertainty as risk: A plug-and-play evidence-guided framework with error-aligned calibration for medical image segmentation

Chaojie Xing, Haolin Zhan, Rencheng Song, Yü Liu

cn (code pays fourni par la source)

Dynamic uncertainty evaluation of axial displacement of optical scanning coordinate measuring machine based on neural network

Yinye Ding, Wenhao Chen, Zeyu Yang, Rencheng Song et autres

Abstract The inner-surface geometry of high-aspect-ratio microholes critically influences the cooling performance of turbine blades in aero-engines. Optical scanning coordinate measuring machines are widely used to inspect such microholes owing to their non-contact operation and high measurement efficiency. During scanning, the axial …

cn (code pays fourni par la source)

Physics-Driven Electromagnetic Inverse Scattering With Limited-Aperture Measurements

Kuiwen Xu, Yuxin Zhang, Rencheng Song, Shasha Hou et autres

Electromagnetic inverse scattering problems (ISPs) in engineering applications are typically constructed based on limited-aperture measurement data, which further exacerbates the inherent nonlinearity and ill-posedness. To alleviate these issues, this article proposes a novel inverse scattering network architecture, the limited aperture network (LA-Net), …

cn (code pays fourni par la source)

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

Jiajie Li, Yu Liu (6938), Rencheng Song, Xun Chen et autres

Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised rPPG methods learn BVP representations without requiring ground-truth physiological annotations, yet their optimization is often hindered by noisy and unstable gradients, resulting in slow convergence …

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

Jiajie Li, Yu Liu (6938), Rencheng Song, Xun Chen et autres

Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised rPPG methods learn BVP representations without requiring ground-truth physiological annotations, yet their optimization is often hindered by noisy and unstable gradients, resulting in slow convergence …

cn (code pays fourni par la source)

Adaptive Physical-Facial Representation Fusion via Subject-Invariant Cross-Modal Prompt Tuning for Video-Based Emotion Recognition

Xi Luo, Jia Li, Rencheng Song, Yu Liu et autres

Emotion recognition from facial videos enables non-contact inference of human emotional states. Although facial expressions are widely used cues, they cannot fully reflect intrinsic affective states. Remote photoplethysmography (rPPG) provides complementary physiological information, but it is highly susceptible to noise and inter-subject …

Adaptive Physical-Facial Representation Fusion via Subject-Invariant Cross-Modal Prompt Tuning for Video-Based Emotion Recognition

Xi Luo, Jia Li, Rencheng Song, Yu Liu et autres

Emotion recognition from facial videos enables non-contact inference of human emotional states. Although facial expressions are widely used cues, they cannot fully reflect intrinsic affective states. Remote photoplethysmography (rPPG) provides complementary physiological information, but it is highly susceptible to noise and inter-subject …

cn (code pays fourni par la source)

SVC 2026: the Second Multimodal Deception Detection Challenge and the First Domain Generalized Remote Physiological Measurement Challenge

Dongliang Zhu, Zhiyi Niu, Bo Zhao, Jiajian Huang et autres

Subtle visual signals, although difficult to perceive with the naked eye, contain important information that can reveal hidden patterns in visual data. These signals play a key role in many applications, including biometric security, multimedia forensics, medical diagnosis, industrial inspection, and affective …

SVC 2026: the Second Multimodal Deception Detection Challenge and the First Domain Generalized Remote Physiological Measurement Challenge

Dongliang Zhu, Zhiyi Niu, Bo Zhao, Jiajian Huang et autres

Subtle visual signals, although difficult to perceive with the naked eye, contain important information that can reveal hidden patterns in visual data. These signals play a key role in many applications, including biometric security, multimedia forensics, medical diagnosis, industrial inspection, and affective …

cn, hk, es (code pays fourni par la source)

Uncertainty-Guided Evidential Deep Learning Schemes in Full-Wave Inverse Scattering Problems

Tingyu Li, Rencheng Song, Xiuzhu Ye

cn (code pays fourni par la source)