The time course of novel visual object recognition.
نویسندگان
چکیده
منابع مشابه
The Time Course of Contextual Effects on Visual Word Recognition
Sentence comprehension depends on continuous prediction of upcoming words. However, when and how contextual information affects the bottom-up streams of visual word recognition is unknown. This study examined the effects of word frequency and contextual predictability (cloze probability of a target word embedded in the sentence) on N1, P200, and N400 components, which are related to various cog...
متن کاملThe time course of visual influences in letter recognition.
This study builds on a specific characteristic of letters of the Roman alphabet-namely, that each letter name is associated with two visual formats, corresponding to their uppercase and lowercase versions. Participants had to read aloud the names of single letters, and event-related potentials (ERPs) for six pairs of visually dissimilar upper- and lowercase letters were recorded. Assuming that ...
متن کاملa computational visual neuroscience model for object recognition
in this study with the inspirations from both neuroscience and computer science, a combinatorial framework for object recognition was proposed having benefited from the advantages of both biologically-inspired hmax_s architecture model for feature extraction and extreme learning machine (elm) as a classifier. hmax model is a feed-forward hierarchical structure resembling the ventral pathway in ...
متن کاملAtypical Time Course of Object Recognition in Autism Spectrum Disorder
In neurotypical observers, it is widely believed that the visual system samples the world in a coarse-to-fine fashion. Past studies on Autism Spectrum Disorder (ASD) have identified atypical responses to fine visual information but did not investigate the time course of the sampling of information at different levels of granularity (i.e. Spatial Frequencies, SF). Here, we examined this question...
متن کاملA novel Local feature descriptor using the Mercator projection for 3D object recognition
Point cloud processing is a rapidly growing research area of computer vision. Introducing of cheap range sensors has made a great interest in the point cloud processing and 3D object recognition. 3D object recognition methods can be divided into two categories: global and local feature-based methods. Global features describe the entire model shape whereas local features encode the neighborhood ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Vision
سال: 2019
ISSN: 1534-7362
DOI: 10.1167/19.10.61a