This research study describes a method that uses neural networks to figure out if a woman has anemia. An artificial neural network is a type of computer network that is based on the real neural networks that make up t...
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Considering that the singleshotmultiboxdetector (SSD) algorithm will be missed or even false when is used to detect the small- and medium-sized objects, in this study, Kullback-Leibler singleshotmultibox detectio...
详细信息
Considering that the singleshotmultiboxdetector (SSD) algorithm will be missed or even false when is used to detect the small- and medium-sized objects, in this study, Kullback-Leibler singleshotmultibox detection (KSSD) object detection algorithm is proposed to improve the accuracy of small- and medium-sized objects detection. Firstly, the details in the detection process are visualised with gradient-weighted class activation mapping technology, and the details of each detection layer are shown in the form of class activation maps. Then it is noted that the phenomenon of the false or missed detection of the objects to be detected on small- and medium-sized objects in the SSD algorithm is related to the regression loss function. Accordingly, Kullback-Leibler border regression loss strategy is adopted and non-maximum suppression algorithm is used to output the final prediction boxes. Experimental results show that compared with the existed detection algorithms, the improved algorithm in this study has higher accuracy and stability, and can significantly improve the detection effect on small- and medium-sized objects.
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