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Multi-objective Identification of UAV Based on Deep Residual Network
| Content Provider | Scilit |
|---|---|
| Author | Qi, Wang Jia Yang, Dai Ji You, Zhai Jin Jin, Ying |
| Copyright Year | 2018 |
| Description | Journal: Iop Conference Series: Materials Science and Engineering Beacuse of the classical RPN (Region Proposal Net) exists the defect of large computation and high time complexity when extracting targets candidate region, a search mode called CRPN (Cascade Region Proposal Network) mode was proposed to ameliorate it in this paper. In order to suppress the degradation phenomenon in deep convolutional neural network training, the residual learning theory was introduced, a novel Mu-ResNet (multi-strapdown deep residual network) was proposed. Combined the Mu-ResNet with CPRN, a network model for multi-target identification of UAV was designed and tested. Compared with the network model that combines ResNet with RPN, the identification accuracy was increased nearly 2 percentage points. |
| Related Links | http://iopscience.iop.org/article/10.1088/1757-899X/428/1/012061/pdf |
| ISSN | 17578981 |
| e-ISSN | 1757899X |
| DOI | 10.1088/1757-899x/428/1/012061 |
| Journal | Iop Conference Series: Materials Science and Engineering |
| Issue Number | 1 |
| Volume Number | 428 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2018-10-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Materials Science and Engineering Industrial Engineering Identification of Uav |
| Content Type | Text |
| Resource Type | Article |
