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  • NAPS Fusion: A framework to overcome experimental data limitations to predict human performance and cognitive task outcomes
    融合框架以克服实验数据限制预测人类表现及认知任务结果

    Nicholas J Napoli,Chad L Stephens,Kellie D Kennedy et al.

    An international journal on information fusion. 2023 Mar:91:15-30. DOI:10.1016/j.inffus.2022.09.016
  • UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection
    基于集成蒙特卡洛 dropout 的不确定性和层次特征融合模型用于新冠肺炎检测

    Moloud Abdar,Soorena Salari,Sina Qahremani et al.

    An international journal on information fusion. 2023 Feb:90:364-381. DOI:10.1016/j.inffus.2022.09.023
  • SPICE-IT: Smart COVID-19 pandemic controlled eradication over NDN-IoT
    基于NDN-IoT的智能COVID-19大流行控制消除技术

    Muhammad Toaha Raza Khan,Malik Muhammad Saad,Muhammad Ashar Tariq et al.

    An international journal on information fusion. 2021 Oct:74:50-64. DOI:10.1016/j.inffus.2021.03.005
  • Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions
    数字医疗中的信息融合的数据规范化：系统性回顾、元分析及未来研究方向

    Yang Nan,Javier Del Ser,Simon Walsh et al.

    An international journal on information fusion. 2022 Jun:82:99-122. DOI:10.1016/j.inffus.2022.01.001
  • Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond

    Guang Yang,Qinghao Ye,Jun Xia

    An international journal on information fusion. 2022 Jan:77:29-52. DOI:10.1016/j.inffus.2021.07.016
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