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We propose a physiologically based intonation model using perceptual relevance.
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However, because we are interested in studying the relationship between other-race perceptual and implicit social biases, we modeled ALPS more on the BFP [4] which probes implicit biases using perceptual primes (e.g., face pictures) as opposed to semantic constructs (e.g., the categories "good" and "bad").
The bimodal synthesis was evaluated using perceptual and subjective evaluations.
This means that when encoding a stereoscopic image, the TAVT model using asymmetric encoding can tolerate greater perceptual distortion than symmetric coding without perceptual quality of the stereoscopic image degradation.
This goal is actually essential for sound quality measurement, as well as for further sound-content-based searching and browsing methods that use perceptual models of environmental sounds and often require measurements based on perceptually relevant acoustical similarities.
We used perceptual thresholds and pupillometry as attentional indices against which to test our model predictions.
The perceptual model used here takes into account advanced features of the HVS identified from psychophysics experiments conducted in our laboratory.
The watermarking scheme is based on the design of a color visual model that is the modification of a perceptual model used in the image coding of gray scale images.
The model order is determined by an iterative adjustment of the Spectral Distortion (SD) measure, which is classic in LPC filter quantization, instead of perceptual criteria adapted to the sinusoidal model used in [22, 23].
Four conditions "related", "unrelated", "perceptual", and "baseline" were modeled using a canonical HRF (hemodynamic response function).
Using FI as the critical decoding variable clearly diverges from models using maximum-likelihood and Bayesian inference methodologies to match perceptual decisions.
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model using structural
model using conventional
model using statistical
model using single
model using fuzzy
model using binary
model using random
model using maximum
model using simple
model using high
model using appropriate
model using different
model using multivariate
model using similar
model using standard
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