Yunfei Li

Distinct macular structural and microvascular alterations differentiate neuromyelitis optica spectrum disorder from myelin oligodendrocyte glycoprotein antibody–associated disease in optic neuritis

Mo Zhang, Yang Liu, Yunfei Li, Yong Li et autres

Introduction Neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD) are among the leading causes of optic neuritis. This study aimed to examine differences in macular retinal structure and microvascular characteristics between affected and unaffected eyes in individuals with …

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Effective degrees of freedom maximization for XL-RIS-assisted near-field communication via hybrid learning-driven optimization

Yaru Li, Wengen Gao, Yunfei Li, Wenlong Jiang

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Joint Secure Localization and Attack Detection for Vehicular Networks With Quantized Measurements: A Variational Bayesian Approach

Yunfei Li, Zhengyao Zhang, Yiting Luo, Weiqiang Tan et autres

This letter addresses the critical challenge of secure and reliable localization in vehicular networks, where stringent bandwidth constraints and malicious attacks coexist. We propose the Quantized Variational Bayesian Learning-based Attack Detection and Secure Localization (QVBL-ADSL) algorithm, a novel method that jointly estimates …

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Completion Time Minimization for ISAC: Joint Trajectory Planning and Power Optimization

Zhanfeng Zhong, Jintao Wang, Zheng Shi, Xu Wang et autres

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Corrigendum to “Semi-automatic paddy rice intensity mapping for southern China with multiple cropping systems”. [Int. J. Appl. Earth Obs. Geoinform. 144C (2025) 104862]

Liangli Meng, Long Yu, Yunfei Li, Ruoque Shen et autres

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Mastering Collaborative Multi-Modal Data Selection: A Focus on Informativeness, Uniqueness, and Representativeness

Qifan Yu, Zhongqi Quentin Yue, Yang Wu, Wenqiao Zhang et autres

Instruction tuning fine-tunes pre-trained Multi-modal Large Language Models (MLLMs) to handle real-world tasks. However, the rapid expansion of visual instruction datasets introduces data redundancy, leading to excessive computational costs. We propose a collaborative framework, DataTailor, which leverages three key principles--informativeness, uniqueness, and …

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Ziv–Zakai Bound for Uplink Time Delay Estimation in RIS-Assisted Massive MIMO Systems

Yunfei Li, Ming Jiang, Zheng Shi, Shaodan Ma et autres

Evaluating time delay estimation performance is critical in reconfigurable intelligent surfaces (RIS)-assisted massive MIMO systems. However, classical performance bounds such as the CRB and BCRB are only locally tight. In this correspondence, we derive a simplified closed-form expression for the globally effective …

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Artificial intelligence in the task of segmentation and classification of brain metastases images: current challenges and future opportunities

Yiheng Hu, Chao Gao, Yiren Wang, Zhongjian Wen et autres

Brain metastases (BM) are common complications of advanced cancer, posing significant diagnostic and therapeutic challenges for clinicians. Therefore, the ability to accurately detect, segment, and classify brain metastases is crucial. This review focuses on the application of artificial intelligence (AI) in brain …

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Double-stage frequency-boost mechanism for high-power wave energy harvesting from ultra-low frequency ocean excitations

Tianyi Tang, Heng Zhao, Yunfei Li, Fusheng Zha et autres

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Variational Bayesian Learning-Based Target Localization and Time Synchronization With Quantized TOA Measurements in Wireless Sensor Networks

Zhengyao Zhang, Yunfei Li, Yiting Luo, Weiqiang Tan et autres

Precise positioning is becoming increasingly crucial across various applications, including rescue operations, intelligent transportation, logistics, and environmental monitoring. However, previous research often assumes that wireless sensor networks are perfectly synchronized or have unlimited communication resources. These assumptions frequently do not align with …

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Ziv-Zakai Bound for DOA Estimation in Massive MIMO Systems With Mixed-Resolution Quantization

Yunfei Li, Ming Jiang, Zheng Shi, Shaodan Ma et autres

The mixed Analog-to-Digital Converter (ADC) architecture is considered a promising solution in balancing the trade-off between high-resolution and low-resolution quantization over the hardware costs, power consumption, and transmission demands in massive multiple-input multiple-output (MIMO) systems. Meanwhile, the Direction of Arrival (DOA) estimation …

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Flow-Based Policy for Online Reinforcement Learning

Lei Lv, Yunfei Li, Yu Luo, Fuchun Sun et autres

We present \textbf{FlowRL}, a novel framework for online reinforcement learning that integrates flow-based policy representation with Wasserstein-2-regularized optimization. We argue that in addition to training signals, enhancing the expressiveness of the policy class is crucial for the performance gains in RL. Flow-based …