An Algorithm for Target Detection Based On Aggregation Multi-Scale Feature
| Autor: | Rongsheng Dong, Yishun Chen |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 1757:012102 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/1757/1/012102 |
| Popis: | In order to alleviate the multi-scale problem caused by the scale change between object instances, pyramids are widely used in target detection. Although these target detectors with characteristic pyramid structure have achieved good results, they have some limitations because they simply construct characteristic pyramids according to the skeleton multi-scale pyramid structure originally used for target classification tasks. In this study, based on M2Det, a multi-scale feature with richer multilevel information is proposed to construct a more effective feature pyramid to detect targets of different scales.First, the basic features with multi-level features will be fused and extracted from the backbone.Then, the basic features are input into the M module, and the features generated by each P module are used as the features of the detection object in the form of dense connection. Finally, the attention mechanism is introduced into the L module to assemble the features with the same scale and construct a feature pyramid for target detection. On the COCO dataset, MLPNet implements the results of AP37.8. |
| Databáze: | OpenAIRE |
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