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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lu Changhua Chang Ningning Fang Rui Liu Chun |
| Copyright Year | 2006 |
| Description | Author affiliation: Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei (Lu Changhua; Chang Ningning) |
| Abstract | This paper deals with the problem of moving objects recognition using Bayesian method. A novel algorithm based on sparse Bayesian classification for the recognition of moving objects is proposed. This approach takes full advantage of sparse Bayesian in solving classification problems. It uses fewer kernel functions in order to reduce the complexity of the computation and resolves the over-fitting problem in recognition system. The experimental results show that this approach distinctly outperforms other classification approaches on this issue. The veracity and velocity are also satisfactory. |
| Starting Page | 135 |
| Ending Page | 139 |
| File Size | 5300240 |
| Page Count | 5 |
| File Format | |
| ISBN | 1424406560 |
| ISSN | 15512541 |
| DOI | 10.1109/MLSP.2006.275536 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-09-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Object recognition Bayesian methods Image recognition Kernel Feature extraction Automatic control Control systems Lighting Support vector machines Support vector machine classification |
| Content Type | Text |
| Resource Type | Article |
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