Zhijie Zhang

HAFM-Net: Hierarchical Alignment Fusion and Mapping for UAV-Based Misaligned RGB-T Salient Object Detection

Zhijie Zhang, Kaihong Chen, Chen Yang, Xicheng Zhang et autres

In unmanned aerial vehicle (UAV) scenarios, RGB-T salient object detection faces several challenges, including cross-modal spatial misalignment, redundant multi-scale features, and weak responses of small objects in cluttered backgrounds, which together degrade fusion effectiveness and localization stability in complex environments. To address …

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Dual characteristics of attentional bias in depression: A three-level meta-analysis

REN Weicong, FAN Junlong, Zhijie Zhang

摘要： 本研究采用三水平元分析方法, 系统考察抑郁个体的注意偏向特征及其潜在调节机制。最终纳入51篇消极注意偏向研究(91个效应量)和33篇积极注意偏向研究(56个效应量)。结果表明, 抑郁个体存在中等程度的消极注意偏向, 同时伴随积极注意偏向的缺失。调节效应分析发现, 任务范式显著影响两类注意偏向的效应量; 刺激类型在消极注意偏向中呈边缘显著作用, 在积极注意偏向中作用显著; 而年龄、样本类型及刺激效价等变量无显著影响。本研究揭示了抑郁个体注意偏向的双重特征, 提示抑郁情绪的改善既依赖于减少对消极信息的过度关注(“减负”), 也依赖于增强对积极信息的注意投入(“增正”), 为完善抑郁认知理论和发展双轨干预策略提供了理论依据。

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Densification, microstructure, mechanical properties, and thermal stability of high-strength Ti-modified Al-Si-Mg-Zr aluminum alloy fabricated by laser-powder bed fusion

Yaoxiang Geng, Zhifa Shan, Jiaming Zhang, Zhijie Zhang

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Quantum Multi-Armed Bandits and Stochastic Linear Bandits Enjoy Logarithmic Regrets

Zongqi Wan, Zhijie Zhang, Tongyang Li, Jialin Zhang et autres

Multi-arm bandit (MAB) and stochastic linear bandit (SLB) are important models in reinforcement learning, and it is well-known that classical algorithms for bandits with time horizon T suffer from the regret of at least the square root of T. In this paper, …

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Time-Varying Gaussian Markov Random Fields Learning for Multivariate Time Series Clustering

Wangxiang Ding, Wenzhong Li, Zhijie Zhang, Wan Chen et autres

Multivariate time series (MTS) clustering is an important technique for discovering co-evolving patterns and interpreting group characteristics in many areas including economics, bioinformatics, data science, etc. Although time series clustering has been widely studied in the past decades, no enough attention has …

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STAD-GAN: Unsupervised Anomaly Detection on Multivariate Time Series with Self-training Generative Adversarial Networks

Zhijie Zhang, Wenzhong Li, Wangxiang Ding, Linming Zhang et autres

Anomaly detection on multivariate time series (MTS) is an important research topic in data mining, which has a wide range of applications in information technology, financial management, manufacturing system, and so on. However, the state-of-the-art unsupervised deep learning models for MTS anomaly …

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Intelligent control of the electrochemical nitrate removal basing on artificial neural network (ANN)

Guangyuan Meng, Liqiang Fang, Yao Yin, Zhijie Zhang et autres

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GaTector: A Unified Framework for Gaze Object Prediction

Binglu Wang, Tao “Eric” Hu, Baoshan Li, Xiaojuan Chen et autres

Gaze object prediction is a newly proposed task that aims to discover the objects being stared at by humans. It is of great application significance but still lacks a unified solution framework. An intuitive solution is to incorporate an object detection branch …

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Ultrathin 3D radial tandem-junction photocathode with a high onset potential of 1.15 V for solar hydrogen production

Shaobo Zhang, Huiting Huang, Zhijie Zhang, Jianyong Feng et autres

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Parallax attention stereo matching network based on the improved group-wise correlation stereo network

Zedong Huang, Zhijie Zhang

Recent stereo matching methods, especially end-to-end deep stereo matching networks, have achieved remarkable performance in the fields of autonomous driving and depth sensing. However, state-of-the-art stereo algorithms, even with the deep neural network framework, still have difficulties at finding correct correspondences in …

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Multi-task sequence learning for performance prediction and KPI mining in database management system

Wan Chen, Wenzhong Li, Wangxiang Ding, Zhijie Zhang et autres

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Unsupervised Human Activity Representation Learning with Multi-task Deep Clustering

Haojie Ma, Zhijie Zhang, Wenzhong Li, Sanglu Lu

Human activity recognition (HAR) based on sensing data from wearable and mobile devices has become an active research area in ubiquitous computing, and it envisions a wide range of application scenarios in mobile social networking, environmental context sensing, health and well-being monitoring, …

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