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ENTITY Dempster–Shafer theory

Dempster–Shafer theory

PulseAugur coverage of Dempster–Shafer theory — every cluster mentioning Dempster–Shafer theory across labs, papers, and developer communities, ranked by signal.

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RECENT · PAGE 1/1 · 6 TOTAL
  1. TOOL · CL_239351 ·

    New active inference method guides autonomous reconnaissance agents

    Researchers have developed a novel active inference method for planning the routes of intelligent agents in autonomous reconnaissance missions. This approach aims to maintain a common operational picture by constructing…

  2. RESEARCH · CL_229491 ·

    Evidential Deep Learning Enhances Multi-Modal Anti-UAV Detection

    Researchers have explored the application of Evidential Deep Learning (EDL) for improving multi-modal anti-UAV detection systems. The first paper investigates EDL heads and Dempster-Shafer fusion on benchmarks like Anti…

  3. TOOL · CL_199988 ·

    New Dempster-Shafer framework enhances evidence fusion with chaos-conflict measurement

    Researchers have developed a new framework for multi-source evidence fusion within the Dempster-Shafer theory, addressing key limitations in existing methods. The proposed system introduces a novel chaos-conflict measur…

  4. TOOL · CL_191347 ·

    New AI architecture ensures calibrated confidence with missing modalities

    Researchers have introduced Modality-Conditioned Conformal Fusion (MCCF), a novel architecture designed to maintain calibrated confidence estimates in multimodal AI systems even when some input modalities are missing. U…

  5. TOOL · CL_100086 ·

    AI system ProMUSE cuts Alzheimer's diagnosis costs with adaptive imaging

    Researchers have developed ProMUSE, a novel AI system designed to improve the early diagnosis of Alzheimer's disease by adaptively incorporating multi-modal data. This system initially uses low-cost clinical assessments…

  6. TOOL · CL_93647 ·

    New AI Framework Enhances Audit Risk Assessment with Uncertainty Modeling

    Researchers have developed UMAR, a novel multi-agent framework designed to improve audit risk assessment by explicitly modeling uncertainty and evidence conflict. UMAR utilizes three specialized agents—MD&A Text Agent, …