作者：
Liu, Y.Cai, K.Liu, C.Zheng, F.Henan Univ
Intelligent Technol & Applicat Engn Res Ctr Henan Key Lab Big Data Anal & Proc Henan Prov Kaifeng 475004 Peoples R China Henan Univ
Coll Comp Sci & Informat Engn Kaifeng 475004 Peoples R China Henan Univ
Intelligent Technol & Applicat Engn Res Ctr Henan Kaifeng 475004 Peoples R China Henan Univ
Key Lab Big Data Anal & Proc Henan Prov Kaifeng 475004 Peoples R China Henan Univ
Engn Lab Spatial Informat Henan Prov Kaifeng 475004 Peoples R China
cross-media semantic retrieval (CSR) and cross-modal semantic mapping are key problems of the multimedia search engine. The cognitive function and neural structure for visual and auditory information process are an im...
详细信息
cross-media semantic retrieval (CSR) and cross-modal semantic mapping are key problems of the multimedia search engine. The cognitive function and neural structure for visual and auditory information process are an important reference for the study of brain-inspired CSR. In this paper, we analyze the hierarchy, the functionality and the structure of visual and auditory in the brain. Considering an idea from deep belief network and hierarchical temporal memory, we presented a brain-inspired intelligent model, called cross-media semantic retrieval based on neuralcomputing of visual and auditory sensation (CSRNCVA). Algorithms based on CSRNCVA were developed. It employs belief propagation algorithms of probabilistic graphical model and hierarchical learning. The experiments show that our model and algorithms can be effectively applied to the CSR. This work provides an important significance for brain-inspired cross-media intelligence framework.
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