Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model
Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
2014-09-01
Volume44Issue:9Pages:1485-1496
SubtypeArticle
AbstractA famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.
KeywordAssociation Biologically Inspired Visual Model Memory Object Recognition
WOS HeadingsScience & Technology ; Technology
WOS KeywordMONKEY INFEROTEMPORAL CORTEX ; OBJECT RECOGNITION ; DECLARATIVE MEMORY ; ATTENTION MODEL ; FACIAL FEATURES ; SEMANTIC MEMORY ; TEMPORAL-LOBE ; FAMILIARITY ; MOTION ; DISCRIMINATION
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000342227500001
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3028
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
AffiliationChinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Qiao, Hong,Li, Yinlin,Tang, Tang,et al. Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model[J]. IEEE TRANSACTIONS ON CYBERNETICS,2014,44(9):1485-1496.
APA Qiao, Hong,Li, Yinlin,Tang, Tang,&Wang, Peng.(2014).Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model.IEEE TRANSACTIONS ON CYBERNETICS,44(9),1485-1496.
MLA Qiao, Hong,et al."Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model".IEEE TRANSACTIONS ON CYBERNETICS 44.9(2014):1485-1496.
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