We have 4 of 12 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This paper formulates subtle GNSS spoofing detection as a causal sequential evidence-modeling problem and proposes a high-order liquid evidence detector that achieves the lowest false-positive rate among the learning-based baselines.
Urban transportation systems generate heterogeneous data, yet these data do not automatically become actionable management intelligence. This chapter adopts a behavior-centered perspective on artificial intelligence (AI), treating mobility records and passenger-generated text as behavioral evidence rather than behavior...
A causal high-order liquid evidence framework for GNSS spoofing detection that achieves the highest F1-scores among the evaluated temporal models on Dataset~1 and Dataset~3, and detects both labeled normal-to-attack transitions within four sampling steps.
Efficient Tuning Before Quantization (ETBQ) is proposed, a pre-conditioning tuning stage for Stochastic Gradient Descent (SGD)-optimized models before PTQ, which improves low-bit PTQ across diverse tasks.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
