scholarly journals Are We Drunk Yet? Motor Versus Cognitive Cues of Subjective Intoxication

2013 ◽  
Vol 38 (2) ◽  
pp. 538-544 ◽  
Author(s):  
Mark A. Celio ◽  
Julie M. Usala ◽  
Stephen A. Lisman ◽  
Gerard E. Johansen ◽  
Courtney S. Vetter-O'Hagen ◽  
...  
Keyword(s):  
Cognitive Cues

Promoting online deliberation quality: cognitive cues matter

2014 ◽  
Vol 17 (10) ◽  
pp. 1177-1195 ◽  
Author(s):  
Edith Manosevitch ◽  
Nili Steinfeld ◽  
Azi Lev-On
Keyword(s):  
Online Deliberation ◽  
Cognitive Cues

scholarly journals Cognitive cues for facilitating computer based interactive task

1999 ◽  
Vol 35 (1Supplement) ◽  
pp. 144a-144a
Author(s):  
Takeshi Ebara ◽  
Toshio Ueno ◽  
Midori Mori ◽  
Yosuke Sanbayashi ◽  
Sadao Horino
Keyword(s):  
Cognitive Cues ◽  
Computer Based ◽  
Interactive Task

The role of meta‐cognitive cues on the comprehension of proficient and poor readers

2020 ◽  
Vol 43 (3) ◽  
pp. 272-289 ◽  
Author(s):  
Christian Soto ◽  
Antonio P. Gutierrez de Blume ◽  
Macarena Andrea Carrasco Bernal ◽  
Marco Antonio Contreras Castro
Keyword(s):  
Poor Readers ◽  
Cognitive Cues

Computational Model for Global Contour Precedence Based on Primary Visual Cortex Mechanisms

2021 ◽  
Vol 18 (3) ◽  
pp. 1-21
Author(s):  
Hui Wei ◽  
Jingmeng Li
Keyword(s):  
Visual Cortex ◽  
Computational Model ◽  
Primary Visual Cortex ◽  
Precedence Effect ◽  
Edge Information ◽  
Proposed Model ◽  
Object Proposals ◽  
Visual Tasks ◽  
Cognitive Cues ◽  
High Level

The edges of an image contains rich visual cognitive cues. However, the edge information of a natural scene usually is only a set of disorganized unorganized pixels for a computer. In psychology, the phenomenon of quickly perceiving global information from a complex pattern is called the global precedence effect (GPE). For example, when one observes the edge map of an image, some contours seem to automatically “pop out” from the complex background. This is a manifestation of GPE on edge information and is called global contour precedence (GCP). The primary visual cortex (V1) is closely related to the processing of edges. In this article, a neural computational model to simulate GCP based on the mechanisms of V1 is presented. There are three layers in the proposed model: the representation of line segments, organization of edges, and perception of global contours. In experiments, the ability to group edges is tested on the public dataset BSDS500. The results show that the grouping performance, robustness, and time cost of the proposed model are superior to those of other methods. In addition, the outputs of the proposed model can also be applied to the generation of object proposals, which indicates that the proposed model can contribute significantly to high-level visual tasks.

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