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Feature Learning for Image Classification via Multiobjective Genetic Programming

文献类型：期刊论文

作者Shao, Ling1,2; Liu, Li2; Li, Xuelong3
刊名ieee transactions on neural networks and learning systems
出版日期2014-07-01
卷号25期号:7页码:1359-1371
关键词Feature extraction genetic programming (GP) image classification multiobjective optimization
ISSN号2162-237x
英文摘要feature extraction is the first and most critical step in image classification. most existing image classification methods use hand-crafted features, which are not adaptive for different image domains. in this paper, we develop an evolutionary learning methodology to automatically generate domain-adaptive global feature descriptors for image classification using multiobjective genetic programming (mogp). in our architecture, a set of primitive 2-d operators are randomly combined to construct feature descriptors through the mogp evolving and then evaluated by two objective fitness criteria, i.e., the classification error and the tree complexity. after the entire evolution procedure finishes, the best-so-far solution selected by the mogp is regarded as the (near-)optimal feature descriptor obtained. to evaluate its performance, the proposed approach is systematically tested on the caltech-101, the mit urban and nature scene, the cmu pie, and jochen triesch static hand posture ii data sets, respectively. experimental results verify that our method significantly outperforms many state-of-the-art hand-designed features and two feature learning techniques in terms of classification accuracy.
WOS标题词science & technology ; technology
类目[WOS]computer science, artificial intelligence ; computer science, hardware & architecture ; computer science, theory & methods ; engineering, electrical & electronic
研究领域[WOS]computer science ; engineering
关键词[WOS]object recognition ; feature-extraction ; scene ; retrieval ; context ; cortex ; shape
收录类别SCI ; EI
语种英语
WOS记录号WOS:000337906300010
公开日期2015-03-18
源URL[http://ir.opt.ac.cn/handle/181661/22385]  
专题西安光学精密机械研究所_光学影像学习与分析中心
作者单位1.Nanjing Univ Informat Sci & Technol, Coll Elect & Informat Engn, Nanjing 210044, Jiangsu, Peoples R China
2.Univ Sheffield, Dept Elect & Elect Engn, Sheffield S1 3JD, S Yorkshire, England
3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning, Xian 710119, Peoples R China
推荐引用方式
GB/T 7714		 Shao, Ling,Liu, Li,Li, Xuelong. Feature Learning for Image Classification via Multiobjective Genetic Programming[J]. ieee transactions on neural networks and learning systems,2014,25(7):1359-1371.
APA Shao, Ling,Liu, Li,&Li, Xuelong.(2014).Feature Learning for Image Classification via Multiobjective Genetic Programming.ieee transactions on neural networks and learning systems,25(7),1359-1371.
MLA Shao, Ling,et al."Feature Learning for Image Classification via Multiobjective Genetic Programming".ieee transactions on neural networks and learning systems 25.7(2014):1359-1371.

入库方式： OAI收割

来源：西安光学精密机械研究所

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