2018
DOI: 10.1167/18.10.1321
|View full text |Cite
|
Sign up to set email alerts
|

Do Semantic Expectations Arising From Masked Word Primes Aid Object Detection At The Earliest Level? Now You See It, Now You Don't

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(2 citation statements)
references
References 0 publications
0
2
0
Order By: Relevance
“…For example, object pairs positioned canonically (e.g., vase on top of a stand) or positioned to interact (e.g., corkscrew facing wine bottle) are perceptually grouped and result in more efficient visual processing. Similarly, objects are better recognized when supported by semantically coherent objects and scenes (Auckland et al, 2007; Biederman, 1972) or when preceded by a semantically related word (Skocypec & Peterson, 2018). Our findings extend these results by demonstrating that advantages derived from experienced likelihoods of real-word object co-occurrences during natural events are stronger than those from learned taxonomic relationships.…”
Section: Discussionmentioning
confidence: 99%
“…For example, object pairs positioned canonically (e.g., vase on top of a stand) or positioned to interact (e.g., corkscrew facing wine bottle) are perceptually grouped and result in more efficient visual processing. Similarly, objects are better recognized when supported by semantically coherent objects and scenes (Auckland et al, 2007; Biederman, 1972) or when preceded by a semantically related word (Skocypec & Peterson, 2018). Our findings extend these results by demonstrating that advantages derived from experienced likelihoods of real-word object co-occurrences during natural events are stronger than those from learned taxonomic relationships.…”
Section: Discussionmentioning
confidence: 99%
“…For instance, the border could be perceived as a joint between two slanted surfaces, the boundary between two colored areas on a two-dimensional surface, or a shadow border). Figure assignment is archetypal object detection because before borders are assigned, patterns are present, but objects are not [ 12 , 31 , 32 , 33 ].…”
Section: The Present Experimentsmentioning
confidence: 99%