Preparation of unstructured data arrays for face recognition in cross-platform registration systems

Author(s):  
Nikolai S. Kazantsev ◽  
Vladimir M. Degtyrev
Author(s):  
Mr. Maheshwar M ◽  
Ms. Maitrayee Mahanta ◽  
Mr. P R Kuber Gupta

The model that is proposed in this article suggests ways to shorten the bridge between human and computer with less human intervention by using inclining concepts such as Machine Learning and Artificial Intelligence. The voice assistants that exists currently in market is capable to perform basic tasks whereas, ARYA on the other hand is a type of voice assistant such as google assistant, cortana etc. which has made it easier for the end users to perform and automate various tasks just using their voice. It has multiple advantages over other voice assistants such as face recognition, cross platform assistance and automate document modifications. These features enhance the Access Control System over the usage of voice assistant and also reduces time and complexity of doing many tasks manually. KEYWORDS-machine learning, artificial intelligence, cross platform, face recognition


2010 ◽  
Vol 69 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Jisien Yang ◽  
Adrian Schwaninger

Configural processing has been considered the major contributor to the face inversion effect (FIE) in face recognition. However, most researchers have only obtained the FIE with one specific ratio of configural alteration. It remains unclear whether the ratio of configural alteration itself can mediate the occurrence of the FIE. We aimed to clarify this issue by manipulating the configural information parametrically using six different ratios, ranging from 4% to 24%. Participants were asked to judge whether a pair of faces were entirely identical or different. The paired faces that were to be compared were presented either simultaneously (Experiment 1) or sequentially (Experiment 2). Both experiments revealed that the FIE was observed only when the ratio of configural alteration was in the intermediate range. These results indicate that even though the FIE has been frequently adopted as an index to examine the underlying mechanism of face processing, the emergence of the FIE is not robust with any configural alteration but dependent on the ratio of configural alteration.


Author(s):  
Chrisanthi Nega

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.


2014 ◽  
Author(s):  
Mario Baldassari ◽  
Justin Kantner ◽  
D. Stephen Lindsay
Keyword(s):  

2010 ◽  
Author(s):  
Margaret Tsai ◽  
Jennifer Groscup
Keyword(s):  

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