Spatial contextual effects in primary visual cortex limit feature representation under crowding
Sign Up to like & getrecommendations! Published in 2020 at "Nature Communications"
DOI: 10.1038/s41467-020-15386-7
Abstract: Crowding is a profound loss of discriminability of visual features, when a target stimulus is surrounded by distractors. Numerous studies of human perception have characterized how crowding depends on the properties of a visual display.… read more here.
Keywords: effects primary; contextual effects; spatial contextual; primary visual ... See more keywords
Where Do Neighborhood Effects End? Moving to Multiscale Spatial Contextual Effects
Sign Up to like & getrecommendations! Published in 2021 at "Annals of the American Association of Geographers"
DOI: 10.1080/24694452.2021.1923455
Abstract: There is no theoretical reason to assume that neighborhood effects operate at a constant single spatial scale across multiple urban settings or over different periods of time. Despite this, many studies use large, single-scale, predefined… read more here.
Keywords: contextual effects; spatial scale; neighborhood effects; spatial contextual ... See more keywords
Cascaded acquisition of spatial contextual cueing
Sign Up to like & getrecommendations! Published in 2023 at "Perception"
DOI: 10.1177/03010066231171357
Abstract: Spatial contextual cueing refers to the facilitation of visual search when invariant spatial configurations of the target and distractors are learned. Using the instance theory of automatization and the reverse hierarchy theory of visual perceptual… read more here.
Keywords: theory; contextual cueing; acquisition spatial; spatial contextual ... See more keywords
Integrating Machine Learning and a Spatial Contextual Algorithm to Detect Wildfire from Himawari-8 Data in Southwest China
Sign Up to like & getrecommendations! Published in 2023 at "Forests"
DOI: 10.3390/f14050919
Abstract: Timely wildfire detection is helpful for fire monitoring and fighting. However, the available wildfire products with high temporal resolutions face problems, such as high omission error and commission error (false alarm) rates. This study proposed… read more here.
Keywords: fire; machine learning; algorithm; spatial contextual ... See more keywords