中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 多模态人工智能系统全国重点实验室
  5. 机器人应用与理论组
Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment

文献类型：期刊论文

作者Lu, Yanfeng1; Jia, Lihao1; Qiao, Hong2; Li, Yi3; Qi, Zongshuai4
刊名INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING
出版日期2019-03-01
卷号17期号:2页码:16
关键词Image recognition classification BIM oriented Gaussian-Hermite moment Gabor features patch selection
ISSN号0219-6913
DOI10.1142/S0219691319400071
通讯作者Lu, Yanfeng(yanfeng.lv@ia.ac.cn)
英文摘要Biologically inspired model (BIM) for image recognition is a robust computational architecture, which has attracted widespread attention. BIM can be described as a four-layer structure based on the mechanisms of the visual cortex. Although the performance of BIM for image recognition is robust, it takes the randomly selected ways for the patch selection, which is sightless, and results in heavy computing burden. To address this issue, we propose a novel patch selection method with oriented Gaussian-Hermite moment (PSGHM), and we enhanced the BIM based on the proposed PSGHM, named as PBIM. In contrast to the conventional BIM which adopts the random method to select patches within the feature representation layers processed by multi-scale Gabor filter banks, the proposed PBIM takes the PSGHM way to extract a small number of representation features while offering promising distinctiveness. To show the effectiveness of the proposed PBIM, experimental studies on object categorization are conducted on the CalTech05, TU Darmstadt (TUD) and GRAZ01 databases. Experimental results demonstrate that the performance of PBIM is a significant improvement on that of the conventional BIM.
WOS关键词OBJECT RECOGNITION ; FACE RECOGNITION ; APPEARANCE ; FEATURES
资助项目National Science Foundation of China[61603389] ; National Natural Science Foundation of China[61502494] ; National Natural Science Foundation of China[61210009] ; Strategic Priority Research Program of the CAS[XDB02080003] ; Development of Science and Technology of Guangdong Province Special Fund Project[2016B090910001]
WOS研究方向Computer Science ; Mathematics
语种英语
WOS记录号WOS:000462661200008
出版者WORLD SCIENTIFIC PUBL CO PTE LTD
资助机构National Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the CAS ; Development of Science and Technology of Guangdong Province Special Fund Project
源URL[http://ir.ia.ac.cn/handle/173211/23486]  
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
通讯作者Lu, Yanfeng
作者单位1.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Beijing 100190, Peoples R China
2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
3.Nanchang Univ, Sch Informat Engn, Nanchang 330031, Jiangxi, Peoples R China
4.Univ Sci & Technol, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714		 Lu, Yanfeng,Jia, Lihao,Qiao, Hong,et al. Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment[J]. INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING,2019,17(2):16.
APA Lu, Yanfeng,Jia, Lihao,Qiao, Hong,Li, Yi,&Qi, Zongshuai.(2019).Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment.INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING,17(2),16.
MLA Lu, Yanfeng,et al."Enhanced biologically inspired model for image recognition based on a novel patch selection method with moment".INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING 17.2(2019):16.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。