Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Recognizing a myriad visual objects rapidly is a hallmark of the primate visual system. Traditional theories of object recognition have focused on how crucial form features, for example, the orientation of edges, may be extracted in early visual cortex and utilized to recognize objects. An alternative view argues that much of early and mid-level visual processing focuses on encoding surface characteristics, for example, texture. Neurophysiological evidence from primate area V4 supports a third alternative - the joint, but independent, encoding of form and texture - that would be advantageous for segmenting objects from the background in natural scenes and for object recognition that is independent of surface texture. Future studies that leverage deep convolutional network models, especially focusing on network failures to match biology and behavior, can advance our insights into how such a joint representation of form and surface properties might emerge in visual cortex.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6876744 | PMC |
http://dx.doi.org/10.1016/j.conb.2019.09.009 | DOI Listing |
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