Hierarchical feature fusion method for multi-target detection of mobile robot
A mobile robot and target detection algorithm technology, which is applied in the field of environmental perception of mobile robots, can solve the problems of low detection ability and insufficient feature extraction, and achieve the effect of improving detection ability and efficiency
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[0029]The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
[0030]As attachedfigure 1 As shown, the present invention is a hierarchical feature fusion method for multi-target detection of mobile robots, which includes the following steps:
[0031]Step 1: Obtain the feature maps initially, and input the images in the data set into the pre-trained and improved VGG-16. The VGG-16 network structure is shown in Figure 2(a): It consists of 13 convolutional layers and 3 fully connected layers. The convolutional layers are Conv1_1, Conv1_2, Conv2_1, Conv2_2, Conv3_1, Conv3_2, Conv3_3, Conv4_1, Conv4_2. , Conv4_3, Conv5_1, Conv5_2, Conv5_3, the fully connected layers are FC6, FC7, FC8; the improved VGG-16 network structure is shown in Figure 2(b): Change the FC6 and FC7 fully connected layers of the VGG-16 network Is the convolutional layer; the feature map T initially obtained in step 11It is the output of the convolution...
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