Research on Machine Learning Method Based on Visual Dynamic Nerve Field View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2013-2016

FUNDING AMOUNT

240000 CNY

ABSTRACT

Machine learning plays an important role in artificial intelligent. One of its basic aims is simulating man's learning activity by computer, which give machine some learning ability to obtain new knowledge and fulfill some tasks. As a result, simulating the structure of nerve system by using research achievements of neurophysiology and cognition science to build new models of nerve system and recognition activity and new learning algorithms is always an important source of machine learning. Based on the features of visual cognitive activities, this project divides the basic visual cognitive activity into different functional levels according to theory and methods of neurophysiology and neurodynamics, which effectively reduces the complexity of modeling visual cognitive system. A new visual cognition model is given based on visual dynamical neural field theory, with which machine learning algorithms based on visual classification and visual clustering activities are also given. These algorithms are then used to solve practical issues like data classification and clustering analysis. Therefore, this project is a beneficial exploration and attempt in introducing neurophysiologic and neurodynamical achievements to building machine learning algorithm and solving practical problems like data mining. More... »

URL

http://npd.nsfc.gov.cn/projectDetail.action?pid=11301096

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