DocumentCode :
1777100
Title :
How computational neuroscience could help improving face recognition systems?
Author :
Karimimehr, Saeed ; Yazdchi, Mohammad Reza
Author_Institution :
Dept. of Eng., Univ. of Isfahan, Isfahan, Iran
fYear :
2014
fDate :
29-30 Oct. 2014
Firstpage :
410
Lastpage :
413
Abstract :
Computational neuroscience is a growing discipline in science, which tries to understand the operations of human brain and inspire from it as a new computational paradigm. Face recognition is an important question both in pattern recognition and neuroscience. In the last few years, neuroscientists found many facts about object recognition in primate´s brain. Here, we propose a cortex inspired face recognition system which uses some findings about the brain such as the operations of feature extractor cells in visual cortex and the function of attention in discarding distracting parts of the images. Now it is the time to merge the knowledge of learning systems with biological findings. The proposed method named Advanced Neurologically Inspires Face recognition (ANIF) system is compared with previous model NIF and some well-known face recognition algorithms within different datasets, which shows remarkable results.
Keywords :
face recognition; feature extraction; learning systems; object recognition; ANIF system; advanced neurologically inspires face recognition system; computational neuroscience; face recognition systems; feature extractor; human brain; learning systems; object recognition; pattern recognition; Brain modeling; Computational modeling; Face; Face recognition; Neuroscience; Signal processing algorithms; Visualization; HMAX; attention; computational neuroscience; face recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Knowledge Engineering (ICCKE), 2014 4th International eConference on
Conference_Location :
Mashhad
Print_ISBN :
978-1-4799-5486-5
Type :
conf
DOI :
10.1109/ICCKE.2014.6993453
Filename :
6993453
Link To Document :
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