Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 机器人应用与理论组

	Introducing Memory and Association Mechanism Into a Biologically Inspired Visual Model
	Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng
刊名	IEEE TRANSACTIONS ON CYBERNETICS
	2014-09-01
卷号	44 期号:9 页码:1485-1496
关键词	Association biologically inspired visual model memory object recognition
英文摘要	A 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.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
研究领域[WOS]	Computer Science
关键词[WOS]	MONKEY INFEROTEMPORAL CORTEX ; OBJECT RECOGNITION ; DECLARATIVE MEMORY ; ATTENTION MODEL ; FACIAL FEATURES ; SEMANTIC MEMORY ; TEMPORAL-LOBE ; FAMILIARITY ; MOTION ; DISCRIMINATION
收录类别	SCI
语种	英语
WOS记录号	WOS:000342227500001
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/3028]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
作者单位	Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 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.