… specific goals and tasks through flexible adaptation [8]. AI … is closer to the human visual
perception mechanism. For those … , change feature extraction, and accuracy assessment should …

… Those results mean differences in driving behavior and safety perception when a vehicle
changes lanes to the left and the right. Therefore, respective models are established. The …

… comparisons or confidence to assess latent memory strength. … We find that these adaptive
instructions increase estimates of … We found strong evidence for this hypothesis, with a Bayes …

… reflects perceptual … Bayesian statistics assess the likelihood of the data under both the null
and the alternative hypotheses (H0 and H1, respectively). In most cases, we report the Bayes …

… , such as over-learning from small perturbations and fast … that perceptual error, arising from
the optimal combination of movement-related cues, is the primary driver of implicit adaptation. …

… by testing whether the inference or incremental classes of … So, we tested whether a model
that leverages Bayesian … the square using an adaptive staircase procedure. After this stage, …

… task data via the combination of “perceptual or learning models” (… to change point detection
theory and in line with Bayesian … and the higher-cognitive domain need to be assessed in the …

… can be obtained by the Bayesian-based EM algorithm [64]. … of different classes fit by the
bayesian-based EM algorithm, … most assessment criteria. For instance, compared with other …

… reasons for the observed changes and resident perception on socio-… Multi-Criteria Evaluation
(MCE) was used to build transition … The study recommend an ecosystem based adaptation …

… Many deep-learning architectures, which allow for adaptive … For the assessment of the
semantic change map, we used the … based on iterative slow feature analysis and Bayesian soft …