163 citations · 291 across the 7 of their papers we have counts for
7 papers
T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIs
Siyang Li, Ziwei Wang, Hanbin Luo +2
Objective: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the human brain and a computer. Due to individual differences and…
Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework
Peter ED Love, Jane Matthews, Weili Fang +3
Explainable artificial intelligence is an emerging and evolving concept. Its impact on construction, though yet to be realised, will be profound in the foreseeable future. Still, X…
Explainable Artificial Intelligence: Precepts, Methods, and Opportunities for Research in Construction
Peter ED Love, Weili Fang, Jane Matthews +3
Explainable artificial intelligence has received limited attention in construction despite its growing importance in various other industrial sectors. In this paper, we provide a n…
Adversarial Attacks and Defenses in Physiological Computing: A Systematic Review
Dongrui Wu, Jiaxin Xu, Weili Fang +5
Physiological computing uses human physiological data as system inputs in real time. It includes, or significantly overlaps with, brain-computer interfaces, affective computing, ad…
Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)
Ziang Liu, Xue Jiang, Hanbin Luo +3
Active learning (AL) selects the most beneficial unlabeled samples to label, and hence a better machine learning model can be trained from the same number of labeled samples. Most…
Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers
Xiao Zhang, Dongrui Wu, Lieyun Ding +4
An electroencephalogram (EEG) based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled indi…
Evaluating resilience in urban transportation systems for sustainability: A systems-based Bayesian network model
Junqing Tang, Hans Heinimann, Ke Han +2
This paper proposes a hierarchical Bayesian network model (BNM) to quantitatively evaluate the resilience of urban transportation infrastructure. Based on systemic thinkings and su…